modify edit

2024-12-08 00:31:50 +08:00 · 2024-12-08 00:28:11 +08:00 · 2024-12-08 00:22:43 +08:00 · 2024-12-08 00:16:03 +08:00 · 2024-12-05 15:20:00 +08:00 · 2024-11-25 14:24:54 +08:00
373 changed files with 48727 additions and 4328 deletions
@@ -9,12 +9,12 @@
 *.bin
 *.idea
 *.csv
+cache
 build
 dist
 dev
 scepter.egg-info
 .readthedocs.yml
-1.9
-MANIFEST.in
 *resources
 *.ipynb_checkpoints*
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@@ -1,4 +1,5 @@
 # -*- coding: utf-8 -*-
+# Copyright (c) Alibaba, Inc. and its affiliates.
 # Configuration file for the Sphinx documentation builder.
 #
 # This file only contains a selection of the most common options. For a full
@@ -29,8 +29,21 @@ Given an original image, image editing aims to generate an image that align with
    <td><img src="../../../asset/images/stylebooth/retrogame.jpeg" width="240"></td>
    <td><img src="../../../asset/images/stylebooth/vangogh.jpeg" width="240"></td>
  </tr>
+  <tr>
+    <td><strong>Origin Image</strong></td>
+    <td><strong>Lowpoly</strong></td>
+    <td><strong>Colored Pencil Art</strong></td>
+    <td><strong>Watercolor</strong></td>
+    <td><strong>misc-disco</strong></td>
+  </tr>
+  <tr>
+    <td><img src="../../../asset/images/stylebooth/mountain.jpg" width="240"></td>
+    <td><img src="../../../asset/images/stylebooth/lowpoly.jpg" width="240"></td>
+    <td><img src="../../../asset/images/stylebooth/colorpencil.jpeg" width="240"></td>
+    <td><img src="../../../asset/images/stylebooth/watercolor.jpeg" width="240"></td>
+    <td><img src="../../../asset/images/stylebooth/disco.jpeg" width="240"></td>
+  </tr>
 </table>
-
 ## Features

 | **Text-Based** | **Exemplar-Based** |
@@ -43,7 +56,7 @@ Given an original image, image editing aims to generate an image that align with
 - More models will be released in the future.

 ## Run StyleBooth
- Code implementation: See model configuration and code based on [🪄SCEPTER](https://github.com/modelscope/scepter).
+- Code implementation: See model configuration and code based on [🪄SCEPTER](https://github.com/modelscope/scepter/blob/main/docs/en/tasks/stylebooth.md).

 - Demo: Try [🖥️SCEPTER Studio](https://github.com/modelscope/scepter/tree/main?tab=readme-ov-file#%EF%B8%8F-scepter-studio).

@@ -92,7 +105,7 @@ class DiffusionInferenceTest(unittest.TestCase):
        output = diff_infer({'prompt': 'Let this image be in the style of sai-lowpoly'},
                            style_edit_image=Image.open('asset/images/inpainting_text_ref/ex4_scene_im.jpg'),
                            style_guide_scale_text=7.5,
-                            style_guide_scale_image=0.5)
+                            style_guide_scale_image=1.5)
        save_path = os.path.join(self.tmp_dir,
                                 'stylebooth_test_lowpoly_cute_dog.png')
        save_image(output['images'], save_path)
@@ -101,3 +114,17 @@ class DiffusionInferenceTest(unittest.TestCase):
 if __name__ == '__main__':
    unittest.main()
 ```
+
+## StyleTuner and De-StyleTuner.
+
+### Base I2I Model.
+
+For style and de-style tuning, we use a private high-resolution I2I model trained with [InstructPix2Pix dataset](https://instruct-pix2pix.eecs.berkeley.edu/) as base model. However, one can try the same tunning process using this [yaml](https://github.com/modelscope/scepter/blob/main/scepter/methods/edit/edit_512_lora.yaml) based on any other I2I model, such as StyleBooth (shown in this yaml), [InstructPix2Pix](https://github.com/timothybrooks/instruct-pix2pix) or [MagicBrush](https://github.com/OSU-NLP-Group/MagicBrush).
+
+### Training Data.
+
+Please check the zips for correct format: [De-Text](https://www.modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=datasets%2Fdetext.zip), [Image2Hed](https://www.modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=datasets%2Fhed_pair.zip), [Image2Depth](https://www.modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=datasets%2Fimage2depth.zip), [Depth2Image](https://www.modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=datasets%2Fdepth2image.zip).
+
+### Launch.
+
+See [code](https://github.com/modelscope/scepter/blob/cbbef4a2da5b66fc33b9f8ece7f2fb4aac9d6e3c/tests/tools/test_train.py#L220) for more information.
@@ -5,7 +5,7 @@ Below are examples for each format, illustrating their details and basic usage.

 ## Modelscope Format

-We use a [custom-stylized dataset](https://modelscope.cn/datasets/damo/style_custom_dataset/summary), which included classes 3D, anime, flat illustration, oil painting, sketch, and watercolor, each with 30 image-text pairs.
+We use a [custom-stylized dataset](https://modelscope.cn/datasets/iic/style_custom_dataset/summary), which included classes 3D, anime, flat illustration, oil painting, sketch, and watercolor, each with 30 image-text pairs.

 ```python
 # pip install modelscope
@@ -16,7 +16,11 @@ print(next(iter(ms_train_dataset)))

 ## CSV Format

-For the data format used by SCEPTER Studio, please refer to [3D_example_csv.zip](https://www.modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=datasets/3D_example_csv.zip).
+For the data format used by SCEPTER Studio, please refer to [3D_example_csv.zip](https://www.modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=datasets/3D_example_csv.zip) and [hed_pair.zip](https://www.modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=datasets%2Fhed_pair.zip).
+```shell
+mkdir -p cache/datasets/ && wget 'https://www.modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=datasets/3D_example_csv.zip' -O cache/datasets/3D_example_csv.zip && unzip cache/datasets/3D_example_csv.zip -d cache/datasets/ && rm cache/datasets/3D_example_csv.zip
+mkdir -p cache/datasets/ && wget 'https://www.modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=datasets/hed_pair.zip' -O cache/datasets/hed_pair.zip && unzip cache/datasets/hed_pair.zip -d cache/datasets/ && rm cache/datasets/hed_pair.zip
+```

 ## TXT Format

@@ -24,3 +28,4 @@ To facilitate starting training in command-line mode, you can use a dataset in t

 ```shell
 mkdir -p cache/datasets/ && wget 'https://www.modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=datasets/3D_example_txt.zip' -O cache/datasets/3D_example_txt.zip && unzip cache/datasets/3D_example_txt.zip -d cache/datasets/ && rm cache/datasets/3D_example_txt.zip
+```
@@ -40,6 +40,6 @@ python scepter/tools/run_inference.py --cfg scepter/methods/scedit/t2i/sd15_512_

 - SCEdit
 ```shell
-python scepter/tools/run_inference.py --cfg scepter/methods/scedit/ctr/sd21_768_sce_ctr_canny.yaml --num_samples 1 --prompt 'a single flower is shown in front of a tree' --save_folder 'test_flower_canny' --image_size 768 --task control --image 'asset/images/flower.jpg' --control_mode canny --pretrained_model ms://damo/scepter_scedit@controllable_model/SD2.1/canny_control/0_SwiftSCETuning/pytorch_model.bin   # canny
-python scepter/tools/run_inference.py --cfg scepter/methods/scedit/ctr/sd21_768_sce_ctr_pose.yaml --num_samples 1 --prompt 'super mario' --save_folder 'test_mario_pose' --image_size 768 --task control --image 'asset/images/pose_source.png' --control_mode source --pretrained_model ms://damo/scepter_scedit@controllable_model/SD2.1/pose_control/0_SwiftSCETuning/pytorch_model.bin   # pose
+python scepter/tools/run_inference.py --cfg scepter/methods/scedit/ctr/sd21_768_sce_ctr_canny.yaml --num_samples 1 --prompt 'a single flower is shown in front of a tree' --save_folder 'test_flower_canny' --image_size 768 --task control --image 'asset/images/flower.jpg' --control_mode canny --pretrained_model ms://iic/scepter_scedit@controllable_model/SD2.1/canny_control/0_SwiftSCETuning/pytorch_model.bin   # canny
+python scepter/tools/run_inference.py --cfg scepter/methods/scedit/ctr/sd21_768_sce_ctr_pose.yaml --num_samples 1 --prompt 'super mario' --save_folder 'test_mario_pose' --image_size 768 --task control --image 'asset/images/pose_source.png' --control_mode source --pretrained_model ms://iic/scepter_scedit@controllable_model/SD2.1/pose_control/0_SwiftSCETuning/pytorch_model.bin   # pose
 ```
@@ -1,4 +1,5 @@
 # -*- coding: utf-8 -*-
+# Copyright (c) Alibaba, Inc. and its affiliates.
 # Configuration file for the Sphinx documentation builder.
 #
 # This file only contains a selection of the most common options. For a full
@@ -6,4 +6,5 @@ dependencies:
  - pip>=20.3
  - numpy>=1.23.1
  - pip:
+      - -r requirements/recommended.txt
      - -r requirements.txt
@@ -2,7 +2,6 @@
 # Copyright (c) Alibaba, Inc. and its affiliates.
 import numpy as np
 import torchvision
-
 from scepter.modules.data.dataset.base_dataset import BaseDataset
 from scepter.modules.data.dataset.registry import DATASETS
 from scepter.modules.utils.config import dict_to_yaml
@@ -0,0 +1,22 @@
+# -*- coding: utf-8 -*-
+# Copyright (c) Alibaba, Inc. and its affiliates.
+import os
+import shutil
+import subprocess
+import sys
+
+if sys.argv[0] == 'install.py':
+    sys.path.append('.')   # for portable version
+
+source_folder = os.path.join(os.path.dirname(__file__), "scepter/workflow")
+current_dir = os.path.dirname(__file__)
+destination_folder = os.path.join(os.path.dirname(current_dir), "ComfyUI-Scepter")
+
+if not os.path.exists(destination_folder):
+    shutil.copytree(source_folder, destination_folder)
+    print(f"{os.path.abspath(source_folder)} copy to {os.path.abspath(destination_folder)} success!")
+else:
+    print(f"{os.path.abspath(destination_folder)} exist.")
+
+# pip install scepter
+subprocess.check_call([sys.executable, '-m', 'pip', 'install', 'scepter'])
@@ -14,10 +14,19 @@ SCEPTER integrates popular community-driven implementations as well as proprieta
 SCEPTER offers 3 core components:
 - [Generative training and inference framework](#tutorials)
 - [Easy implementation of popular approaches](#currently-supported-approaches)
- [Interactive user interface: SCEPTER Studio](#launch)
+- [Interactive user interface: SCEPTER Studio & Comfy UI](#launch)


 ## 🎉 News
+- [🔥🔥🔥2024.11]: We're excited to announce the upcoming release of the [ACE-0.6b-1024px](https://huggingface.co/scepter-studio/ACE-0.6B-1024px) model, 
+which significantly enhances image generation quality compared with [ACE-0.6b-512px](https://huggingface.co/scepter-studio/ACE-0.6B-512px). The detailed documents can be found at [ACE repo](https://github.com/ali-vilab/ACE.git).
+At the same time, based on the editing results of ACE, combined with the powerful text-to-image capabilities of the [FLUX-dev](https://huggingface.co/black-forest-labs/FLUX.1-dev) model through SDEdit as an image quality refiner, the quality of image editing can be further enhanced.
+- [🔥2024.11]: Supports video files, video annotation, caption translation in data management, and inference & training of the [CogVideoX](https://arxiv.org/abs/2408.06072).
+- [2024.10]: We are pleased to announce the release of the code for [ACE](https://arxiv.org/abs/2410.00086), supporting Customized Training / Comfy UI Workflow / gradio-based ChatBot Interface. 
+- [2024.10]: Support for inference and tuning with [FLUX](https://huggingface.co/black-forest-labs/FLUX.1-dev), as well as for building [ComfyUI](https://github.com/comfyanonymous/ComfyUI) workflows using this framework.
+- [2024.09]: We introduce **ACE**, an **A**ll-round **C**reator and **E**ditor adept at executing a diverse array of image editing tasks tailored to your specifications. Built upon the cutting-edge Diffusion Transformer architecture, ACE has been extensively trained on a comprehensive dataset to seamlessly interpret and execute any natural language instruction. For further information, please consult the [project page](https://ali-vilab.github.io/ace-page/).
+- [2024.07]: Support the inference and training of open-source generative models based on the [DiT](https://arxiv.org/abs/2212.09748) architecture, such as [SD3](https://arxiv.org/pdf/2403.03206) and [PixArt](https://arxiv.org/abs/2310.00426).
+- [2024.05]: Introducing SCEPTER v1, supporting customized image edit tasks! Simply provide 10 image pairs, SCEPTER will tune an edit tuner for your own Image-to-Image tasks, like `Clay Style`, `De-Text`, `Segmentation`, etc.
 - [2024.04]: New [StyleBooth](https://ali-vilab.github.io/stylebooth-page/) demo on SCEPTER Studio for`Text-Based Style Editing`.
 - [2024.03]: We optimize the training UI and checkpoint management. New [LAR-Gen](https://arxiv.org/abs/2403.19534) model has been added on SCEPTER Studio, supporting `zoom-out`, `virtual try on`, `inpainting`.
 - [2024.02]: We release new SCEdit controllable image synthesis models for SD v2.1 and SD XL. Multiple strategies applied to accelerate inference time for SCEPTER Studio.
@@ -27,61 +36,177 @@ SCEPTER offers 3 core components:
 - [2023.12]: We release [🪄SCEPTER](https://github.com/modelscope/scepter/) library.


-## 🖼 Gallery for Recent Works

-### StyleBooth
-<table>
+
+## 🪄ACE
+
+ACE is a unified foundational model framework that supports a wide range of visual generation tasks. By defining CU for unifying multi-modal inputs across different tasks and incorporating long-context CU, we introduce historical contextual information into visual generation tasks, paving the way for ChatGPT-like dialog systems in visual generation.
+
+[![Watch the demo](https://ali-vilab.github.io/ace-page/static/images/tasks.png)](https://ali-vilab.github.io/ace-page/)
+
+### ACE Models
+|    **Model**     |                                                                                                                                                                                                            **Status**                                                                                                                                                                                                             | 
+|:----------------:|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
+|  ACE-0.6B-512px  |          [![Demo link](https://img.shields.io/badge/Demo-ACE_Chat-purple)](https://huggingface.co/spaces/scepter-studio/ACE-Chat)<br>[![ModelScope link](https://img.shields.io/badge/ModelScope-Model-blue)](https://www.modelscope.cn/models/iic/ACE-0.6B-512px)  [![HuggingFace link](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Model-yellow)](https://huggingface.co/scepter-studio/ACE-0.6B-512px)          |
+| ACE-0.6B-1024px  | [![Demo link](https://img.shields.io/badge/Demo-ACE_Refiner_Chat-purple)](https://huggingface.co/spaces/scepter-studio/ACE-Refiner-Chat)<br>[![ModelScope link](https://img.shields.io/badge/ModelScope-Model-blue)](https://www.modelscope.cn/models/iic/ACE-0.6B-1024px)  [![HuggingFace link](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Model-yellow)](https://huggingface.co/scepter-studio/ACE-0.6B-1024px) |             |
+| ACE-12B-FLUX-dev |                                                                                                                                                                                                            Coming Soon                                                                                                                                                                                                            |
+### ACE Training
+
+We offer a demonstration training YAML that enables the end-to-end training of ACE using a toy dataset. For a comprehensive overview of the hyperparameter configurations, please consult `scepter/methods/edit/dit_ace_0.6b_512.yaml`.
+
+#### Prepare datasets
+
+Please find the dataset class located in `scepter/modules/data/dataset/ms_dataset.py`,
+designed to facilitate end-to-end training using an open-source toy dataset.
+Download a dataset zip file from [modelscope](https://www.modelscope.cn/models/iic/scepter/resolve/master/datasets/hed_pair.zip), and then extract its contents into the `cache/datasets/` directory.
+
+Should you wish to prepare your own datasets, we recommend consulting `scepter/modules/data/dataset/ms_dataset.py` for detailed guidance on the required data format.
+
+#### Prepare initial weight
+The ACE checkpoint has been uploaded to both ModelScope and HuggingFace platforms:
+* [ModelScope](https://www.modelscope.cn/models/iic/ACE-0.6B-512px)
+* [HuggingFace](https://huggingface.co/scepter-studio/ACE-0.6B-512px)
+
+In the provided training YAML configuration, we have designated the Modelscope URL as the default checkpoint URL. Should you wish to transition to Hugging Face, you can effortlessly achieve this by modifying the PRETRAINED_MODEL value within the YAML file (replace the prefix "ms://iic" to "hf://scepter-studio").
+
+
+#### Start training
+
+You can easily start training procedure by executing the following command:
+```bash
+# ACE-0.6B-512px
+PYTHONPATH=. python scepter/tools/run_train.py --cfg scepter/methods/edit/dit_ace_0.6b_512.yaml
+# ACE-0.6B-1024px
+PYTHONPATH=. python scepter/tools/run_train.py --cfg scepter/methods/edit/dit_ace_0.6b_1024.yaml
+```
+
+### ACE Chat Bot
+
+We have developed a chatbot interface utilizing Gradio, designed to convert user input in natural language into visually captivating images that align semantically with the specified instructions. You can easily access this functionality by launching Scepter Studio with the following command:
+```bash
+PYTHONPATH=. python scepter/tools/webui.py --cfg scepter/methods/studio/scepter_ui.yaml --language zh --tab chatbot
+```
+Upon starting, you will find a "ChatBot" tab within the Gradio application, which serves as a chat-based interface to handle any requests related to image editing or generation.
+
+### ACE ComfyUI Workflow
+
+![Workflow](https://github.com/ali-vilab/ace-page/raw/main/assets/comfyui/ace_example.jpg)
+
+<table><tbody>
  <tr>
-    <td><strong>Origin Image</strong><br>Gold Dragon Tuner</td>
-    <td><strong>Graffiti Art</strong></td>
-    <td><strong>Adorable Kawaii</strong></td>
-    <td><strong>game-retro game</strong></td>
-    <td><strong>Vincent van Gogh</strong></td>
+    <th align="center" colspan="4">ACE Workflow Examples</th>
  </tr>
  <tr>
-    <td><img src="asset/images/scedit/tuner_gold_dragon.jpeg" width="240"></td>
-    <td><img src="asset/images/stylebooth/graffiti.jpeg" width="240"></td>
-    <td><img src="asset/images/stylebooth/kawaii.jpeg" width="240"></td>
-    <td><img src="asset/images/stylebooth/retrogame.jpeg" width="240"></td>
-    <td><img src="asset/images/stylebooth/vangogh.jpeg" width="240"></td>
+    <th align="center" colspan="1">Control</th>
+    <th align="center" colspan="1">Semantic</th>
+    <th align="center" colspan="1">Element</th>
  </tr>
+  <tr>
+    <td>
+      <a href="https://github.com/ali-vilab/ace-page/raw/main/assets/comfyui/ace_control.png" target="_blank">
+        <img src="https://github.com/ali-vilab/ace-page/raw/main/assets/comfyui/ace_control.png" width="200">
+      </a>
+    </td>
+    <td>
+      <a href="https://github.com/ali-vilab/ace-page/raw/main/assets/comfyui/ace_semantic.png" target="_blank">
+        <img src="https://github.com/ali-vilab/ace-page/raw/main/assets/comfyui/ace_semantic.png" width="200">
+      </a>
+    </td>
+    <td>
+      <a href="https://github.com/ali-vilab/ace-page/raw/main/assets/comfyui/ace_element.png" target="_blank">
+        <img src="https://github.com/ali-vilab/ace-page/raw/main/assets/comfyui/ace_element.png" width="200">
+      </a>
+    </td>
+  </tr>
+</tbody>
 </table>

-<table>
+## 🖼 Gallery for Recent Works
+
+### FLUX Tuners
+
+<table><tbody>
  <tr>
-    <td><strong>Origin Image</strong></td>
-    <td><strong>Lowpoly</strong></td>
-    <td><strong>Colored Pencil Art</strong></td>
-    <td><strong>Watercolor</strong></td>
-    <td><strong>misc-disco</strong></td>
+    <th align="center" colspan="3">Yarn Style</th>
+    <th align="center" colspan="3">Soft Watercolor Style</th>
  </tr>
  <tr>
-    <td><img src="asset/images/stylebooth/mountain.jpg" width="240"></td>
-    <td><img src="asset/images/stylebooth/lowpoly.jpg" width="240"></td>
-    <td><img src="asset/images/stylebooth/colorpencil.jpeg" width="240"></td>
-    <td><img src="asset/images/stylebooth/watercolor.jpeg" width="240"></td>
-    <td><img src="asset/images/stylebooth/disco.jpeg" width="240"></td>
+    <td><img src="asset/images/flux_tuner/flux_tuner_2_1.webp" width="200"></td>
+    <td><img src="asset/images/flux_tuner/flux_tuner_2_2.webp" width="200"></td>
+    <td><img src="asset/images/flux_tuner/flux_tuner_2_3.webp" width="200"></td>
+    <td><img src="asset/images/flux_tuner/flux_tuner_1_1.webp" width="200"></td>
+    <td><img src="asset/images/flux_tuner/flux_tuner_1_2.webp" width="200"></td>
+    <td><img src="asset/images/flux_tuner/flux_tuner_1_3.webp" width="200"></td>
  </tr>
+  <tr>
+    <th align="center" colspan="3">Travel Style</th>
+    <th align="center" colspan="3">WuKong Style</th>
+  </tr>
+  <tr>
+    <td><img src="asset/images/flux_tuner/flux_tuner_3_1.webp" width="200"></td>
+    <td><img src="asset/images/flux_tuner/flux_tuner_3_2.webp" width="200"></td>
+    <td><img src="asset/images/flux_tuner/flux_tuner_3_3.webp" width="200"></td>
+    <td><img src="asset/images/flux_tuner/flux_tuner_4_1.webp" width="200"></td>
+    <td><img src="asset/images/flux_tuner/flux_tuner_4_2.webp" width="200"></td>
+    <td><img src="asset/images/flux_tuner/flux_tuner_4_3.webp" width="200"></td>
+  </tr>
+</tbody>
+</table>
+
+### ComfyUI Workflow
+
+![Workflow](asset/workflow/workflow.jpg)
+
+<table><tbody>
+  <tr>
+    <th align="center" colspan="4">Example Workflow Case</th>
+  </tr>
+  <tr>
+    <th align="center" colspan="1">Base</th>
+    <th align="center" colspan="1">+Mantra</th>
+    <th align="center" colspan="1">+Tuner</th>
+    <th align="center" colspan="1">+Control</th>
+  </tr>
+  <tr>
+    <td>
+      <a href="asset/workflow/sdxl_base.json" target="_blank">
+        <img src="asset/workflow/sdxl_base.jpg" width="200">
+      </a>
+    </td>
+    <td>
+      <a href="asset/workflow/sdxl_base_mantra.json" target="_blank">
+        <img src="asset/workflow/sdxl_base_mantra.jpg" width="200">
+      </a>
+    </td>
+    <td>
+      <a href="asset/workflow/sdxl_base_mantra_tuner.json" target="_blank">
+        <img src="asset/workflow/sdxl_base_mantra_tuner.jpg" width="200">
+      </a>
+    </td>
+    <td>
+      <a href="asset/workflow/sdxl_base_mantra_tuner_control.json" target="_blank">
+        <img src="asset/workflow/sdxl_base_mantra_tuner_control.jpg" width="200">
+      </a>
+    </td>
+  </tr>
+</tbody>
 </table>


 ## 🛠️ Installation

- Create new environment
+- Create new environment with `conda` command:

 ```shell
 conda env create -f environment.yaml
 conda activate scepter
 ```
- We recommend installing the specific version of PyTorch and accelerate toolbox [xFormers](https://pypi.org/project/xformers/). You can install these recommended version by pip:

+- Install with `pip` command:
+
+We recommend installing the specific version of PyTorch and accelerate toolbox [xFormers](https://pypi.org/project/xformers/). You can install these recommended version by pip:
 ```shell
 pip install -r requirements/recommended.txt
-```
-
- Install SCEPTER by the `pip` command:
-
-```shell
 pip install scepter
 ```

@@ -101,15 +226,17 @@ pip install scepter
 ### Currently supported approaches

 |            Tasks             |                    Methods                     | Links                                                                                                                                                                                                                                                       |
-|:----------------------------:|:--------------------------------------------:|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-|   Text-to-image generation   |                   SD v1.5                    | [![Hugging Face Repo](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Repo-blue)](https://huggingface.co/runwayml/stable-diffusion-v1-5)                                                                                                         |
-|   Text-to-image generation   |                   SD v2.1                    | [![Hugging Face Repo](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Repo-blue)](https://huggingface.co/runwayml/stable-diffusion-v1-5)                                                                                                         |
-|   Text-to-image generation   |                    SD-XL                     | [![Hugging Face Repo](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Repo-blue)](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0)                                                                                               |
+|:----------------------------:|:----------------------------------------------:|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+|   Text-to-image Generation   |                    SD v1.5                     | [![Hugging Face Repo](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Repo-blue)](https://huggingface.co/runwayml/stable-diffusion-v1-5)                                                                                                         |
+|   Text-to-image Generation   |                    SD v2.1                     | [![Hugging Face Repo](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Repo-blue)](https://huggingface.co/runwayml/stable-diffusion-v1-5)                                                                                                         |
+|   Text-to-image Generation   |                     SD-XL                      | [![Hugging Face Repo](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Repo-blue)](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0)                                                                                               |
+|   Text-to-image Generation   |                      FLUX                      | [![Hugging Face Repo](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Repo-blue)](https://huggingface.co/black-forest-labs/FLUX.1-dev)                                                                                               |
 |       Efficient Tuning       |                      LoRA                      | [![Arxiv   link](https://img.shields.io/static/v1?label=arXiv&message=LoRA&color=red&logo=arxiv)](https://arxiv.org/abs/2106.09685)                                                                                                                         |
 |       Efficient Tuning       |             Res-Tuning(NeurIPS23)              | [![Arxiv   link](https://img.shields.io/static/v1?label=arXiv&message=Res-Tuing&color=red&logo=arxiv)](https://arxiv.org/abs/2310.19859) [![Page link](https://img.shields.io/badge/Page-ResTuning-Gree)](https://res-tuning.github.io/)                    |
-| Controllable image synthesis | [🌟SCEdit(CVPR24)](docs/en/tasks/scedit.md)  | [![Arxiv   link](https://img.shields.io/static/v1?label=arXiv&message=SCEdit&color=red&logo=arxiv)](https://arxiv.org/abs/2312.11392)   [![Page link](https://img.shields.io/badge/Page-SCEdit-Gree)](https://scedit.github.io/)                            |
-|        Image editing         |     [🌟LAR-Gen](docs/en/tasks/largen.md)     | [![Arxiv   link](https://img.shields.io/static/v1?label=arXiv&message=LARGen&color=red&logo=arxiv)](https://arxiv.org/abs/2403.19534)   [![Page link](https://img.shields.io/badge/Page-LARGen-Gree)](https://ali-vilab.github.io/largen-page/)             |
-|        Image editing         |  [🌟StyleBooth](docs/en/tasks/stylebooth.md) | [![Arxiv   link](https://img.shields.io/static/v1?label=arXiv&message=StyleBooth&color=red&logo=arxiv)](https://arxiv.org/abs/2404.12154)   [![Page link](https://img.shields.io/badge/Page-StyleBooth-Gree)](https://ali-vilab.github.io/stylebooth-page/) |
+| Controllable Image Synthesis |  [🌟SCEdit(CVPR24)](docs/en/tasks/scedit.md)   | [![Arxiv   link](https://img.shields.io/static/v1?label=arXiv&message=SCEdit&color=red&logo=arxiv)](https://arxiv.org/abs/2312.11392)   [![Page link](https://img.shields.io/badge/Page-SCEdit-Gree)](https://scedit.github.io/)                            |
+|        Image Editing         |      [🌟LAR-Gen](docs/en/tasks/largen.md)      | [![Arxiv   link](https://img.shields.io/static/v1?label=arXiv&message=LARGen&color=red&logo=arxiv)](https://arxiv.org/abs/2403.19534)   [![Page link](https://img.shields.io/badge/Page-LARGen-Gree)](https://ali-vilab.github.io/largen-page/)             |
+|        Image Editing         |  [🌟StyleBooth](docs/en/tasks/stylebooth.md)   | [![Arxiv   link](https://img.shields.io/static/v1?label=arXiv&message=StyleBooth&color=red&logo=arxiv)](https://arxiv.org/abs/2404.12154)   [![Page link](https://img.shields.io/badge/Page-StyleBooth-Gree)](https://ali-vilab.github.io/stylebooth-page/) |
+| Image Generation and Editing | [🌟ACE](https://ali-vilab.github.io/ace-page/) | [![Arxiv   link](https://img.shields.io/static/v1?label=arXiv&message=ACE&color=red&logo=arxiv)](https://arxiv.org/abs/2410.00086)   [![Page link](https://img.shields.io/badge/Page-ACE-Gree)](https://ali-vilab.github.io/ace-page/) [![Demo link](https://img.shields.io/badge/Demo-ACE-purple)](https://huggingface.co/spaces/scepter-studio/ACE-Chat) <br> [![ModelScope link](https://img.shields.io/badge/ModelScope-Model-blue)](https://www.modelscope.cn/models/iic/ACE-0.6B-512px)  [![HuggingFace link](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Model-yellow)](https://huggingface.co/scepter-studio/ACE-0.6B-512px) |


 ## 🖥️ SCEPTER Studio
@@ -132,8 +259,6 @@ The startup of **SCEPTER Studio** eliminates the need for manual downloading and
 Depending on the network and hardware situation, the initial startup usually requires 15-60 minutes, primarily involving the download and processing of SDv1.5, SDv2.1, and SDXL models.
 Therefore, subsequent startups will become much faster (about one minute) as downloading is no longer required.

-To support the sharing and downloading of models,
-please make sure that you have installed **zip** and Git Large File Storage (**git lfs**).
 ### Usage Demo

 |              [Image Editing](https://www.modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=assets%2Fscepter_studio%2Fimage_editing_20240419.webm)              |                [Training](https://www.modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=assets%2Fscepter_studio%2Ftraining_20240419.webm)                 |              [Model Sharing](https://www.modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=assets%2Fscepter_studio%2Fmodel_sharing_20240419.webm)               |             [Model Inference](https://www.modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=assets%2Fscepter_studio%2Fmodel_inference_20240419.webm)              |             [Data Management](https://www.modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=assets%2Fscepter_studio%2Fdata_management_20240419.webm)              |
@@ -142,9 +267,27 @@ please make sure that you have installed **zip** and Git Large File Storage (**g

 ### Modelscope Studio & Huggingface Space

-We deploy a work studio on Modelscope that includes only the inference tab, please refer to [ms_scepter_studio](https://www.modelscope.cn/studios/damo/scepter_studio/summary) and [hf_scepter_studio](https://huggingface.co/spaces/modelscope/scepter_studio)
+We deploy a work studio on Modelscope that includes only the inference tab, please refer to [ms_scepter_studio](https://www.modelscope.cn/studios/iic/scepter_studio/summary) and [hf_scepter_studio](https://huggingface.co/spaces/modelscope/scepter_studio)


+
+## ⚙️️ ComfyUI Workflow
+
+We support the use of all models in the ComfyUI Workflow through the following methods:
+
+1) Automatic installation directly via the ComfyUI Manager by searching for the **ComfyUI-Scepter** node.
+2) Manually install by moving custom_nodes from Scepter to ComfyUI.
+```shell
+git clone https://github.com/modelscope/scepter.git
+cd path/to/scepter
+pip install -e .
+cp -r path/to/scepter/workflow/ path/to/ComfyUI/custom_nodes/ComfyUI-Scepter
+cd path/to/ComfyUI
+python main.py
+```
+
+**Note**: You can use the nodes by dragging the sample images into ComfyUI. Additionally, our nodes can automatically pull models from ModelScope or HuggingFace by selecting the *model_source* field, or you can place the already downloaded models in a local path.
+
 ## 🔍 Learn More

 - [Alibaba TongYi Vision Intelligence Lab](https://github.com/ali-vilab)
@@ -177,4 +320,4 @@ This project is licensed under the [Apache License (Version 2.0)](https://github


 ## Acknowledgement
-Thanks to [Stability-AI](https://github.com/Stability-AI), [SWIFT library](https://github.com/modelscope/swift/) and [Fooocus](https://github.com/lllyasviel/Fooocus) for their awesome work.
+Thanks to [Stability-AI](https://github.com/Stability-AI), [SWIFT library](https://github.com/modelscope/swift/), [Fooocus](https://github.com/lllyasviel/Fooocus) and [ComfyUI](https://github.com/comfyanonymous/ComfyUI) for their awesome work.
@@ -1,8 +1,9 @@
 albumentations
+beautifulsoup4
 bezier
 einops
-modelscope
-ms-swift>=2.0.1
+modelscope[framework]<=1.20.1
+ms-swift
 numpy
 open_clip_torch
 opencv-python
@@ -11,5 +12,7 @@ oss2>=2.15.0
 pycocotools
 pyyaml>=5.3.1
 scikit-image
+scikit-learn
+sentencepiece
 torchsde
-transformers
+transformers<=4.46.3
@@ -1,4 +1,5 @@
 git+https://github.com/cocodataset/panopticapi.git
-torch==2.0.1
-torchvision==0.15.2
-xformers==0.0.21
+torch==2.4.1
+torchvision==.19.1
+flash-attn==2.5.8
+xformers==0.0.28
@@ -1,5 +1,6 @@
-bitsandbytes
-gradio>=3.47.1,<4.0.0
+bitsandbytes<=0.44.1
+gradio
+gradio_imageslider
 imagehash
 psutil
 tiktoken
@@ -0,0 +1,161 @@
+ENV:
+  BACKEND: nccl
+  SEED: 2024
+#
+SOLVER:
+  NAME: ACESolver
+  RESUME_FROM:
+  LOAD_MODEL_ONLY: True
+  USE_FSDP: False
+  SHARDING_STRATEGY:
+  USE_AMP: True
+  DTYPE: float16
+  CHANNELS_LAST: True
+  MAX_STEPS: 500
+  MAX_EPOCHS: -1
+  NUM_FOLDS: 1
+  ACCU_STEP: 1
+  EVAL_INTERVAL: 50
+  RESCALE_LR: False
+  #
+  WORK_DIR: ./cache/save_data/ace_0.6b_1024
+  LOG_FILE: std_log.txt
+  #
+  FILE_SYSTEM:
+    - NAME: "HuggingfaceFs"
+      TEMP_DIR: ./cache/cache_data
+    - NAME: "LocalFs"
+      TEMP_DIR: ./cache/cache_data
+    - NAME: "ModelscopeFs"
+      TEMP_DIR: ./cache/cache_data
+
+  #
+  MODEL:
+    NAME: LatentDiffusionACE
+    PRETRAINED_MODEL:
+    IGNORE_KEYS: [ ]
+    SCALE_FACTOR: 0.18215
+    SIZE_FACTOR: 8
+    DECODER_BIAS: 0.5
+    DEFAULT_N_PROMPT:
+    USE_EMA: True
+    EVAL_EMA: False
+    TEXT_IDENTIFIER: [ '{image}', '{image1}', '{image2}', '{image3}', '{image4}', '{image5}', '{image6}', '{image7}', '{image8}', '{image9}' ]
+    USE_TEXT_POS_EMBEDDINGS: True
+    #
+    DIFFUSION:
+      NAME: BaseDiffusion
+      PREDICTION_TYPE: eps
+      MIN_SNR_GAMMA:
+      NOISE_SCHEDULER:
+        NAME: LinearScheduler
+        NUM_TIMESTEPS: 1000
+        BETA_MIN: 0.0001
+        BETA_MAX: 0.02
+    #
+    DIFFUSION_MODEL:
+      NAME: ACE
+      PRETRAINED_MODEL: ms://iic/ACE-0.6B-1024px@models/dit/ace_0.6b_1024px.pth
+      IGNORE_KEYS: [ ]
+      PATCH_SIZE: 2
+      IN_CHANNELS: 4
+      HIDDEN_SIZE: 1152
+      DEPTH: 28
+      NUM_HEADS: 16
+      MLP_RATIO: 4.0
+      PRED_SIGMA: True
+      DROP_PATH: 0.0
+      WINDOW_DIZE: 0
+      Y_CHANNELS: 4096
+      MAX_SEQ_LEN: 4096
+      QK_NORM: True
+      USE_GRAD_CHECKPOINT: True
+      ATTENTION_BACKEND: flash_attn
+    #
+    FIRST_STAGE_MODEL:
+      NAME: AutoencoderKL
+      EMBED_DIM: 4
+      PRETRAINED_MODEL: ms://iic/ACE-0.6B-1024px@models/vae/vae.bin
+      IGNORE_KEYS: []
+      #
+      ENCODER:
+        NAME: Encoder
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 4
+        DOUBLE_Z: True
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+      #
+      DECODER:
+        NAME: Decoder
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 4
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+        GIVE_PRE_END: False
+        TANH_OUT: False
+    #
+    COND_STAGE_MODEL:
+      NAME: T5EmbedderHF
+      PRETRAINED_MODEL: ms://iic/ACE-0.6B-1024px@models/text_encoder/t5-v1_1-xxl/
+      TOKENIZER_PATH: ms://iic/ACE-0.6B-1024px@models/tokenizer/t5-v1_1-xxl
+      LENGTH: 120
+      T5_DTYPE: bfloat16
+      ADDED_IDENTIFIER: [ '{image}', '{caption}', '{mask}', '{ref_image}', '{image1}', '{image2}', '{image3}', '{image4}', '{image5}', '{image6}', '{image7}', '{image8}', '{image9}' ]
+      CLEAN: whitespace
+      USE_GRAD: False
+    LOSS:
+      NAME: ReconstructLoss
+      LOSS_TYPE: l2
+  #
+  SAMPLE_ARGS:
+    SAMPLER: ddim
+    SAMPLE_STEPS: 20
+    GUIDE_SCALE: 4.5
+    GUIDE_RESCALE: 0.5
+  #
+  OPTIMIZER:
+    NAME: AdamW
+    LEARNING_RATE: 1e-7
+    EPS: 1e-10
+    WEIGHT_DECAY: 5e-4
+  #
+  TRAIN_DATA:
+    NAME: ImageTextPairMSDatasetForACE
+    MODE: train
+    MS_DATASET_NAME: cache/datasets/hed_pair
+    MS_DATASET_NAMESPACE: ""
+    MS_DATASET_SPLIT: "train"
+    MS_DATASET_SUBNAME: ""
+    PROMPT_PREFIX: ""
+    REPLACE_STYLE: False
+    MAX_SEQ_LEN: 4096
+    PIN_MEMORY: True
+    BATCH_SIZE: 1
+    NUM_WORKERS: 1
+    SAMPLER:
+      NAME: LoopSampler
+  #
+  TRAIN_HOOKS:
+    -
+      NAME: BackwardHook
+      PRIORITY: 0
+    -
+      NAME: LogHook
+      LOG_INTERVAL: 50
+    -
+      NAME: CheckpointHook
+      INTERVAL: 100
+    -
+      NAME: ProbeDataHook
+      PROB_INTERVAL: 100
@@ -0,0 +1,161 @@
+ENV:
+  BACKEND: nccl
+  SEED: 2024
+#
+SOLVER:
+  NAME: ACESolver
+  RESUME_FROM:
+  LOAD_MODEL_ONLY: True
+  USE_FSDP: False
+  SHARDING_STRATEGY:
+  USE_AMP: True
+  DTYPE: float16
+  CHANNELS_LAST: True
+  MAX_STEPS: 500
+  MAX_EPOCHS: -1
+  NUM_FOLDS: 1
+  ACCU_STEP: 1
+  EVAL_INTERVAL: 50
+  RESCALE_LR: False
+  #
+  WORK_DIR: ./cache/save_data/ace_0.6b_512
+  LOG_FILE: std_log.txt
+  #
+  FILE_SYSTEM:
+    - NAME: "HuggingfaceFs"
+      TEMP_DIR: ./cache/cache_data
+    - NAME: "LocalFs"
+      TEMP_DIR: ./cache/cache_data
+    - NAME: "ModelscopeFs"
+      TEMP_DIR: ./cache/cache_data
+
+  #
+  MODEL:
+    NAME: LatentDiffusionACE
+    PRETRAINED_MODEL:
+    IGNORE_KEYS: [ ]
+    SCALE_FACTOR: 0.18215
+    SIZE_FACTOR: 8
+    DECODER_BIAS: 0.5
+    DEFAULT_N_PROMPT:
+    USE_EMA: True
+    EVAL_EMA: False
+    TEXT_IDENTIFIER: [ '{image}', '{image1}', '{image2}', '{image3}', '{image4}', '{image5}', '{image6}', '{image7}', '{image8}', '{image9}' ]
+    USE_TEXT_POS_EMBEDDINGS: True
+    #
+    DIFFUSION:
+      NAME: BaseDiffusion
+      PREDICTION_TYPE: eps
+      MIN_SNR_GAMMA:
+      NOISE_SCHEDULER:
+        NAME: LinearScheduler
+        NUM_TIMESTEPS: 1000
+        BETA_MIN: 0.0001
+        BETA_MAX: 0.02
+    #
+    DIFFUSION_MODEL:
+      NAME: ACE
+      PRETRAINED_MODEL: ms://iic/ACE-0.6B-512px@models/dit/ace_0.6b_512px.pth
+      IGNORE_KEYS: [ ]
+      PATCH_SIZE: 2
+      IN_CHANNELS: 4
+      HIDDEN_SIZE: 1152
+      DEPTH: 28
+      NUM_HEADS: 16
+      MLP_RATIO: 4.0
+      PRED_SIGMA: True
+      DROP_PATH: 0.0
+      WINDOW_DIZE: 0
+      Y_CHANNELS: 4096
+      MAX_SEQ_LEN: 1024
+      QK_NORM: True
+      USE_GRAD_CHECKPOINT: True
+      ATTENTION_BACKEND: flash_attn
+    #
+    FIRST_STAGE_MODEL:
+      NAME: AutoencoderKL
+      EMBED_DIM: 4
+      PRETRAINED_MODEL: ms://iic/ACE-0.6B-512px@models/vae/vae.bin
+      IGNORE_KEYS: []
+      #
+      ENCODER:
+        NAME: Encoder
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 4
+        DOUBLE_Z: True
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+      #
+      DECODER:
+        NAME: Decoder
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 4
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+        GIVE_PRE_END: False
+        TANH_OUT: False
+    #
+    COND_STAGE_MODEL:
+      NAME: T5EmbedderHF
+      PRETRAINED_MODEL: ms://iic/ACE-0.6B-512px@models/text_encoder/t5-v1_1-xxl/
+      TOKENIZER_PATH: ms://iic/ACE-0.6B-512px@models/tokenizer/t5-v1_1-xxl
+      LENGTH: 120
+      T5_DTYPE: bfloat16
+      ADDED_IDENTIFIER: [ '{image}', '{caption}', '{mask}', '{ref_image}', '{image1}', '{image2}', '{image3}', '{image4}', '{image5}', '{image6}', '{image7}', '{image8}', '{image9}' ]
+      CLEAN: whitespace
+      USE_GRAD: False
+    LOSS:
+      NAME: ReconstructLoss
+      LOSS_TYPE: l2
+  #
+  SAMPLE_ARGS:
+    SAMPLER: ddim
+    SAMPLE_STEPS: 20
+    GUIDE_SCALE: 4.5
+    GUIDE_RESCALE: 0.5
+  #
+  OPTIMIZER:
+    NAME: AdamW
+    LEARNING_RATE: 1e-7
+    EPS: 1e-10
+    WEIGHT_DECAY: 5e-4
+  #
+  TRAIN_DATA:
+    NAME: ImageTextPairMSDatasetForACE
+    MODE: train
+    MS_DATASET_NAME: cache/datasets/hed_pair
+    MS_DATASET_NAMESPACE: ""
+    MS_DATASET_SPLIT: "train"
+    MS_DATASET_SUBNAME: ""
+    PROMPT_PREFIX: ""
+    REPLACE_STYLE: False
+    MAX_SEQ_LEN: 1024
+    PIN_MEMORY: True
+    BATCH_SIZE: 1
+    NUM_WORKERS: 1
+    SAMPLER:
+      NAME: LoopSampler
+  #
+  TRAIN_HOOKS:
+    -
+      NAME: BackwardHook
+      PRIORITY: 0
+    -
+      NAME: LogHook
+      LOG_INTERVAL: 50
+    -
+      NAME: CheckpointHook
+      INTERVAL: 100
+    -
+      NAME: ProbeDataHook
+      PROB_INTERVAL: 100
@@ -0,0 +1,250 @@
+ENV:
+  BACKEND: nccl
+SOLVER:
+  NAME: LatentDiffusionSolver
+  RESUME_FROM:
+  LOAD_MODEL_ONLY: True
+  USE_FSDP: False
+  SHARDING_STRATEGY:
+  USE_AMP: True
+  DTYPE: float16
+  CHANNELS_LAST: True
+  MAX_STEPS: 2000
+  MAX_EPOCHS: -1
+  NUM_FOLDS: 1
+  ACCU_STEP: 1
+  EVAL_INTERVAL: 100
+  #
+  WORK_DIR: ./cache/save_data/edit_512_lora
+  LOG_FILE: std_log.txt
+  #
+  FILE_SYSTEM:
+    NAME: "ModelscopeFs"
+    TEMP_DIR: "./cache/cache_data"
+  #
+  TUNER:
+    -
+      NAME: SwiftLoRA
+      R: 64
+      LORA_ALPHA: 64
+      LORA_DROPOUT: 0.0
+      BIAS: "none"
+      TARGET_MODULES: model.*(to_q|to_k|to_v|to_out.0|net.0.proj|net.2)$
+  #
+  MODEL:
+    NAME: LatentDiffusionEdit
+    PARAMETERIZATION: eps
+    TIMESTEPS: 1000
+    MIN_SNR_GAMMA:
+    ZERO_TERMINAL_SNR: False
+    PRETRAINED_MODEL: ms://iic/stylebooth@models/stylebooth-tb-5000-0.bin
+    IGNORE_KEYS: [ ]
+    CONCAT_NO_SCALE_FACTOR: True
+    SCALE_FACTOR: 0.18215
+    SIZE_FACTOR: 8
+    # DEFAULT_N_PROMPT: 'lowres, error, worst quality, low quality, jpeg artifacts, ugly, duplicate, morbid, mutilated, out of frame, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, mutation, deformed, blurry, dehydrated, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, username, watermark, signature'
+    DEFAULT_N_PROMPT:
+    SCHEDULE_ARGS:
+      "NAME": "scaled_linear"
+      "BETA_MIN": 0.00085
+      "BETA_MAX": 0.012
+    USE_EMA: False
+    #
+    DIFFUSION_MODEL:
+      NAME: DiffusionUNet
+      IN_CHANNELS: 8
+      OUT_CHANNELS: 4
+      MODEL_CHANNELS: 320
+      NUM_HEADS: 8
+      NUM_RES_BLOCKS: 2
+      ATTENTION_RESOLUTIONS: [ 4, 2, 1 ]
+      CHANNEL_MULT: [ 1, 2, 4, 4 ]
+      CONV_RESAMPLE: True
+      DIMS: 2
+      USE_CHECKPOINT: False
+      USE_SCALE_SHIFT_NORM: False
+      RESBLOCK_UPDOWN: False
+      USE_SPATIAL_TRANSFORMER: True
+      TRANSFORMER_DEPTH: 1
+      CONTEXT_DIM: 768
+      DISABLE_MIDDLE_SELF_ATTN: False
+      USE_LINEAR_IN_TRANSFORMER: False
+      PRETRAINED_MODEL:
+      IGNORE_KEYS: []
+    #
+    FIRST_STAGE_MODEL:
+      NAME: AutoencoderKL
+      EMBED_DIM: 4
+      PRETRAINED_MODEL:
+      IGNORE_KEYS: []
+      BATCH_SIZE: 4
+      #
+      ENCODER:
+        NAME: Encoder
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 4
+        DOUBLE_Z: True
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+      #
+      DECODER:
+        NAME: Decoder
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 4
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+        GIVE_PRE_END: False
+        TANH_OUT: False
+    #
+    TOKENIZER:
+      NAME: ClipTokenizer
+      PRETRAINED_PATH: ms://AI-ModelScope/clip-vit-large-patch14
+      LENGTH: 77
+      CLEAN: True
+    #
+    COND_STAGE_MODEL:
+      NAME: FrozenCLIPEmbedder
+      FREEZE: True
+      LAYER: last
+      PRETRAINED_MODEL: ms://AI-ModelScope/clip-vit-large-patch14
+    #
+    LOSS:
+      NAME: ReconstructLoss
+      LOSS_TYPE: l2
+  #
+  SAMPLE_ARGS:
+    SAMPLER: ddim
+    SAMPLE_STEPS: 50
+    SEED: 2023
+    GUIDE_SCALE: #7.5
+      image: 1.5
+      text: 7.5
+    GUIDE_RESCALE: 0.5
+    DISCRETIZATION: trailing
+    IMAGE_SIZE: [512, 512]
+    RUN_TRAIN_N: False
+  #
+  OPTIMIZER:
+    NAME: AdamW
+    LEARNING_RATE: 0.064
+    BETAS: [ 0.9, 0.999 ]
+    EPS: 1e-8
+    WEIGHT_DECAY: 1e-2
+    AMSGRAD: False
+  #
+  TRAIN_DATA:
+    NAME: ImageTextPairMSDataset
+    MODE: train
+    MS_DATASET_NAME: cache/datasets/hed_pair
+    MS_DATASET_NAMESPACE: ""
+    MS_DATASET_SPLIT: "train"
+    MS_DATASET_SUBNAME: ""
+    PROMPT_PREFIX: ""
+    REPLACE_STYLE: False
+    PIN_MEMORY: True
+    BATCH_SIZE: 1
+    NUM_WORKERS: 4
+    SAMPLER:
+      NAME: LoopSampler
+    TRANSFORMS:
+      - NAME: LoadImageFromFileList
+        FILE_KEYS: ['img_path', 'src_path']
+        RGB_ORDER: RGB
+        BACKEND: pillow
+      - NAME: FlexibleResize
+        INTERPOLATION: bilinear
+        SIZE: [ 512, 512 ]
+        INPUT_KEY: [ 'img', 'src' ]
+        OUTPUT_KEY: [ 'img', 'src' ]
+        BACKEND: pillow
+      - NAME: FlexibleCenterCrop
+        SIZE: [ 512, 512 ]
+        INPUT_KEY: [ 'img', 'src' ]
+        OUTPUT_KEY: [ 'img', 'src' ]
+        BACKEND: pillow
+      - NAME: ImageToTensor
+        INPUT_KEY: [ 'img', 'src' ]
+        OUTPUT_KEY: [ 'img', 'src' ]
+        BACKEND: pillow
+      - NAME: Normalize
+        MEAN: [ 0.5,  0.5,  0.5 ]
+        STD: [ 0.5,  0.5,  0.5 ]
+        INPUT_KEY: [ 'img', 'src' ]
+        OUTPUT_KEY: [ 'image', 'condition_cat' ]
+        BACKEND: torchvision
+      - NAME: Select
+        KEYS: [ 'image', 'condition_cat', 'prompt' ]
+        META_KEYS: [ 'data_key' ]
+  #
+  TRAIN_HOOKS:
+    -
+      NAME: BackwardHook
+      PRIORITY: 0
+    -
+      NAME: LogHook
+      LOG_INTERVAL: 50
+    -
+      NAME: CheckpointHook
+      INTERVAL: 1000
+    -
+      NAME: ProbeDataHook
+      PROB_INTERVAL: 100
+
+  EVAL_DATA:
+    NAME: Text2ImageDataset
+    MODE: eval
+    PROMPT_FILE:
+    PROMPT_DATA: [ "Convert to an edge map#;#cache/datasets/hed_pair/images/src_001.jpeg" ]
+    IMAGE_SIZE: [ 512, 512 ]
+    FIELDS: [ "prompt", "src_path" ]
+    DELIMITER: '#;#'
+    PROMPT_PREFIX: ''
+    PIN_MEMORY: True
+    BATCH_SIZE: 1
+    NUM_WORKERS: 4
+    TRANSFORMS:
+      - NAME: LoadImageFromFileList
+        FILE_KEYS: [ 'src_path' ]
+        RGB_ORDER: RGB
+        BACKEND: pillow
+      - NAME: FlexibleResize
+        INTERPOLATION: bilinear
+        SIZE: [ 512, 512 ]
+        INPUT_KEY: [ 'src' ]
+        OUTPUT_KEY: [ 'src' ]
+        BACKEND: pillow
+      - NAME: FlexibleCenterCrop
+        SIZE: [ 512, 512 ]
+        INPUT_KEY: [ 'src' ]
+        OUTPUT_KEY: [ 'src' ]
+        BACKEND: pillow
+      - NAME: ImageToTensor
+        INPUT_KEY: [ 'src' ]
+        OUTPUT_KEY: [ 'src' ]
+        BACKEND: pillow
+      - NAME: Normalize
+        MEAN: [ 0.5,  0.5,  0.5 ]
+        STD: [ 0.5,  0.5,  0.5 ]
+        INPUT_KEY: [ 'src' ]
+        OUTPUT_KEY: [ 'condition_cat' ]
+        BACKEND: torchvision
+      - NAME: Select
+        KEYS: [ 'condition_cat', 'prompt' ]
+        META_KEYS: [ 'image_size' ]
+  EVAL_HOOKS:
+    -
+      NAME: ProbeDataHook
+      PROB_INTERVAL: 100
+      SAVE_LAST: True
+      SAVE_NAME_PREFIX: 'step'
+      SAVE_PROBE_PREFIX: 'image'
@@ -11,7 +11,7 @@ SOLVER:
  # NUM_FOLDS DESCRIPTION: Num folds for training. TYPE: int default: 0
  NUM_FOLDS: 1
  # WORK_DIR DESCRIPTION: Save dir of the training log or model. TYPE: str default: ''
-  WORK_DIR: ./exp12/
+  WORK_DIR: ./cache/save_data/example/
  LOG_FILE: std_log.txt
  # EVAL_INTERVAL DESCRIPTION: Eval the model interval. TYPE: int default: 1
  EVAL_INTERVAL: 1
@@ -102,7 +102,7 @@ SOLVER:
    # DATASET DESCRIPTION: the public dataset name TYPE: str default: 'cifar10'
    DATASET: cifar10
    # DATA_ROOT DESCRIPTION: the download data save path TYPE: str default: ''
-    DATA_ROOT: ./local_data/cifar10
+    DATA_ROOT: ./cache/cache_data/cifar10
    # MODE DESCRIPTION: test TYPE: str default: test
    MODE: test
    # PIN_MEMORY DESCRIPTION: pin_memory for data loader TYPE: bool default: False
@@ -0,0 +1,235 @@
+ENV:
+  BACKEND: nccl
+  SEED: 42
+  TENSOR_PARALLEL_SIZE: 1
+  PIPELINE_PARALLEL_SIZE: 1
+  SYS_ENVS:
+    TORCH_CUDNN_V8_API_ENABLED: '1'
+    TOKENIZERS_PARALLELISM: 'false'
+    TF_CPP_MIN_LOG_LEVEL: '3'
+    PYTORCH_CUDA_ALLOC_CONF: 'expandable_segments:True'
+#
+SOLVER:
+  NAME: LatentDiffusionVideoSolver
+  MAX_STEPS: 2000
+  USE_AMP: True
+  DTYPE: bfloat16
+  USE_FAIRSCALE: False
+  USE_FSDP: True
+  LOAD_MODEL_ONLY: False
+  RESUME_FROM:
+  WORK_DIR: ./cache/save_data/dit_cogvideox_2b_lora
+  LOG_FILE: std_log.txt
+  EVAL_INTERVAL: 100
+  LOG_TRAIN_NUM: 4
+  ENABLE_GRADSCALER: False
+  USE_SCALER: False
+  FPS: 8
+  SHARDING_STRATEGY: full_shard
+  FSDP_REDUCE_DTYPE: float32
+  FSDP_BUFFER_DTYPE: float32
+  FSDP_SHARD_MODULES: [ 'model', 'cond_stage_model.model']
+  SAVE_MODULES: [ 'model', 'cond_stage_model.model']
+  TRAIN_MODULES: ['model']
+  #
+  FILE_SYSTEM:
+    NAME: "ModelscopeFs"
+    TEMP_DIR: "./cache/cache_data"
+  #
+  TUNER:
+    - NAME: SwiftLoRA
+      R: 64
+      LORA_ALPHA: 64
+      LORA_DROPOUT: 0.0
+      BIAS: "none"
+      TARGET_MODULES: "model.*(.to_k|.to_q|.to_v|.to_out.0)$"
+  #
+  MODEL:
+    NAME: LatentDiffusionCogVideoX
+    PRETRAINED_MODEL:
+    PARAMETERIZATION: v
+    TIMESTEPS: 1000
+    MIN_SNR_GAMMA: 3.0
+    ZERO_TERMINAL_SNR: True
+    SCALE_FACTOR_SPATIAL: 8
+    SCALE_FACTOR_TEMPORAL: 4
+    SCALING_FACTOR_IMAGE: 1.15258426
+    IGNORE_KEYS: [ ]
+    DEFAULT_N_PROMPT:
+    USE_EMA: False
+    EVAL_EMA: False
+    DIFFUSION:
+      NAME: BaseDiffusion
+      PREDICTION_TYPE: v
+      NOISE_SCHEDULER:
+        NAME: ScaledLinearScheduler
+        BETA_MIN: 0.00085
+        BETA_MAX: 0.012
+        SNR_SHIFT_SCALE: 3.0
+        RESCALE_BETAS_ZERO_SNR: True
+      DIFFUSION_SAMPLERS:
+        NAME: DDIMSampler
+        DISCRETIZATION_TYPE: trailing
+        ETA: 0.0
+    #
+    DIFFUSION_MODEL:
+      NAME: CogVideoXTransformer3DModel
+      DTYPE: bfloat16
+      PRETRAINED_MODEL: ms://AI-ModelScope/CogVideoX-2b@transformer/diffusion_pytorch_model.safetensors
+      NUM_ATTENTION_HEADS: 30
+      ATTENTION_HEAD_DIM: 64
+      IN_CHANNELS: 16
+      OUT_CHANNELS: 16
+      FLIP_SIN_TO_COS: True
+      FREQ_SHIFT: 0
+      TIME_EMBED_DIM: 512
+      TEXT_EMBED_DIM: 4096
+      NUM_LAYERS: 30
+      DROPOUT: 0.0
+      ATTENTION_BIAS: True
+      SAMPLE_WIDTH: 90
+      SAMPLE_HEIGHT: 60
+      SAMPLE_FRAMES: 49
+      PATCH_SIZE: 2
+      TEMPORAL_COMPRESSION_RATIO: 4
+      MAX_TEXT_SEQ_LENGTH: 226
+      ACTIVATION_FN: "gelu-approximate"
+      TIMESTEP_ACTIVATION_FN: "silu"
+      NORM_ELEMENTWISE_AFFINE: True
+      NORM_EPS: 1e-5
+      SPATIAL_INTERPOLATION_SCALE: 1.875
+      TEMPORAL_INTERPOLATION_SCALE: 1.0
+      USE_ROTARY_POSITIONAL_EMBEDDINGS: False
+      USE_LEARNED_POSITIONAL_EMBEDDINGS: False
+      GRADIENT_CHECKPOINTING: False
+    #
+    FIRST_STAGE_MODEL:
+      NAME: AutoencoderKLCogVideoX
+      DTYPE: bfloat16
+      PRETRAINED_MODEL: ms://AI-ModelScope/CogVideoX-2b@vae/diffusion_pytorch_model.safetensors
+      SAMPLE_HEIGHT: 480
+      SAMPLE_WIDTH: 720
+      USE_QUANT_CONV: False
+      USE_POST_QUANT_CONV: False
+      USE_SLICING: True
+      USE_TILING: True
+      GRADIENT_CHECKPOINTING: False
+      ENCODER:
+        NAME: CogVideoXEncoder3D
+        IN_CHANNELS: 3
+        OUT_CHANNELS: 16
+        UP_BLOCK_TYPES: [ "CogVideoXDownBlock3D", "CogVideoXDownBlock3D", "CogVideoXDownBlock3D", "CogVideoXDownBlock3D" ]
+        BLOCK_OUT_CHANNELS: [ 128, 256, 256, 512 ]
+        LAYERS_PER_BLOCK: 3
+        ACT_FN: "silu"
+        NORM_EPS: 1e-6
+        NORM_NUM_GROUPS: 32
+        DROPOUT: 0.0
+        PAD_MODE: "first"
+        TEMPORAL_COMPRESSION_RATIO: 4
+        GRADIENT_CHECKPOINTING: False
+      DECODER:
+        NAME: CogVideoXDecoder3D
+        IN_CHANNELS: 16
+        OUT_CHANNELS: 3
+        UP_BLOCK_TYPES: [ "CogVideoXUpBlock3D", "CogVideoXUpBlock3D", "CogVideoXUpBlock3D", "CogVideoXUpBlock3D" ]
+        BLOCK_OUT_CHANNELS: [ 128, 256, 256, 512 ]
+        LAYERS_PER_BLOCK: 3
+        ACT_FN: "silu"
+        NORM_EPS: 1e-6
+        NORM_NUM_GROUPS: 32
+        DROPOUT: 0.0
+        PAD_MODE: "first"
+        TEMPORAL_COMPRESSION_RATIO: 4
+        GRADIENT_CHECKPOINTING: False
+    #
+    COND_STAGE_MODEL:
+      NAME: T5EmbedderHF
+      PRETRAINED_MODEL: ms://AI-ModelScope/t5-v1_1-xxl
+      TOKENIZER_PATH: ms://AI-ModelScope/t5-v1_1-xxl
+      LENGTH: 226
+      CLEAN:
+      USE_GRAD: False
+    #
+    LOSS:
+      NAME: ReconstructLoss
+      LOSS_TYPE: l2
+  #
+  SAMPLE_ARGS:
+    SAMPLER: ddim
+    SAMPLE_STEPS: 50
+    SEED: 42
+    GUIDE_SCALE: 6.0
+    GUIDE_RESCALE: 0.0
+    NUM_FRAMES: 49
+  #
+  OPTIMIZER:
+    NAME: Adam
+    LEARNING_RATE: 1e-3
+    BETAS: [ 0.9, 0.95 ]
+    EPS: 1e-8
+    WEIGHT_DECAY: 0.0
+    AMSGRAD: False
+  #
+#  LR_SCHEDULER:
+#    NAME: StepAnnealingLR
+#    WARMUP_STEPS: 200
+#    TOTAL_STEPS: 2000
+#    DECAY_MODE: 'cosine'
+  #
+  TRAIN_DATA:
+    NAME: VideoGenDataset
+    MODE: train
+    PIN_MEMORY: True
+    BATCH_SIZE: 1
+    NUM_WORKERS: 4
+    PROMPT_PREFIX: 'DISNEY '
+    SAMPLER:
+      NAME: MixtureOfSamplers
+      SUB_SAMPLERS:
+        - NAME: MultiLevelBatchSampler
+          PROB: 1.0
+          FIELDS: [ "video_path", "prompt" ]
+          DELIMITER: '#;#'
+          PATH_PREFIX: cache/datasets/Disney-VideoGeneration-Dataset/
+          INDEX_FILE: cache/datasets/Disney-VideoGeneration-Dataset/index.jsonl
+    TRANSFORMS:
+      - NAME: Select
+        KEYS: [ 'video', "prompt" ]
+        META_KEYS: [ ]
+  #
+  EVAL_DATA:
+    NAME: Text2ImageDataset
+    MODE: eval
+    PROMPT_FILE:
+    PROMPT_DATA: [ "A girl riding a bike.", "A panda, dressed in a small, red jacket and a tiny hat, sits on a wooden stool in a serene bamboo forest. The panda's fluffy paws strum a miniature acoustic guitar, producing soft, melodic tunes. Nearby, a few other pandas gather, watching curiously and some clapping in rhythm. Sunlight filters through the tall bamboo, casting a gentle glow on the scene. The panda's face is expressive, showing concentration and joy as it plays. The background includes a small, flowing stream and vibrant green foliage, enhancing the peaceful and magical atmosphere of this unique musical performance." ]
+    IMAGE_SIZE: [ 480, 720 ]
+    FIELDS: [ "prompt" ]
+    DELIMITER: '#;#'
+    PROMPT_PREFIX: 'DISNEY '
+    PIN_MEMORY: True
+    BATCH_SIZE: 1
+    USE_NUM: 8
+    NUM_WORKERS: 4
+    TRANSFORMS:
+      - NAME: Select
+        KEYS: [ 'index', 'prompt' ]
+        META_KEYS: [ 'image_size' ]
+  #
+  TRAIN_HOOKS:
+    - NAME: ProbeDataHook
+      PROB_INTERVAL: 100
+      PRIORITY: 0
+    - NAME: BackwardHook
+      PRIORITY: 10
+    - NAME: LogHook
+      LOG_INTERVAL: 10
+      PRIORITY: 20
+    - NAME: CheckpointHook
+      INTERVAL: 1000
+      PRIORITY: 40
+  #
+  EVAL_HOOKS:
+    - NAME: ProbeDataHook
+      PROB_INTERVAL: 100
+      PRIORITY: 0
@@ -0,0 +1,266 @@
+ENV:
+  BACKEND: nccl
+  SEED: 42
+  TENSOR_PARALLEL_SIZE: 1
+  PIPELINE_PARALLEL_SIZE: 1
+  SYS_ENVS:
+    TORCH_CUDNN_V8_API_ENABLED: '1'
+    TOKENIZERS_PARALLELISM: 'false'
+    TF_CPP_MIN_LOG_LEVEL: '3'
+    PYTORCH_CUDA_ALLOC_CONF: 'expandable_segments:True'
+#
+SOLVER:
+  NAME: LatentDiffusionVideoSolver
+  MAX_STEPS: 2000
+  USE_AMP: True
+  DTYPE: bfloat16
+  USE_FAIRSCALE: False
+  USE_FSDP: True
+  LOAD_MODEL_ONLY: False
+  ENABLE_GRADSCALER: False
+  USE_SCALER: False
+  RESUME_FROM:
+  WORK_DIR: ./cache/save_data/dit_cogvideox_5b_i2v_lora
+  LOG_FILE: std_log.txt
+  EVAL_INTERVAL: 100
+  LOG_TRAIN_NUM: 4
+  FPS: 8
+  SHARDING_STRATEGY: full_shard
+  FSDP_REDUCE_DTYPE: float32
+  FSDP_BUFFER_DTYPE: float32
+  FSDP_SHARD_MODULES: [ 'model', 'cond_stage_model.model']
+  SAVE_MODULES: [ 'model', 'cond_stage_model.model']
+  TRAIN_MODULES: ['model']
+  #
+  FILE_SYSTEM:
+    NAME: "ModelscopeFs"
+    TEMP_DIR: "./cache/cache_data"
+  #
+  TUNER:
+    - NAME: SwiftLoRA
+      R: 64
+      LORA_ALPHA: 64
+      LORA_DROPOUT: 0.0
+      BIAS: "none"
+      TARGET_MODULES: "model.*(.to_k|.to_q|.to_v|.to_out.0)$"
+  #
+  MODEL:
+    NAME: LatentDiffusionCogVideoX
+    PRETRAINED_MODEL:
+    PARAMETERIZATION: v
+    TIMESTEPS: 1000
+    MIN_SNR_GAMMA: 3.0
+    ZERO_TERMINAL_SNR: True
+    SCALE_FACTOR_SPATIAL: 8
+    SCALE_FACTOR_TEMPORAL: 4
+    SCALING_FACTOR_IMAGE: 0.7  # 5b diff
+    NOISED_IMAGE_DROPOUT: 0.05
+    IGNORE_KEYS: [ ]
+    DEFAULT_N_PROMPT:
+    USE_EMA: False
+    EVAL_EMA: False
+    DIFFUSION:
+      NAME: BaseDiffusion
+      PREDICTION_TYPE: v
+      NOISE_SCHEDULER:
+        NAME: ScaledLinearScheduler
+        BETA_MIN: 0.00085
+        BETA_MAX: 0.012
+        SNR_SHIFT_SCALE: 1.0  # 5b diff
+        RESCALE_BETAS_ZERO_SNR: True
+      DIFFUSION_SAMPLERS:
+        NAME: DDIMSampler
+        DISCRETIZATION_TYPE: trailing
+        ETA: 0.0
+    #
+    DIFFUSION_MODEL:
+      NAME: CogVideoXTransformer3DModel
+      DTYPE: bfloat16
+      PRETRAINED_MODEL: # 5b-I2V diff
+        - ms://AI-ModelScope/CogVideoX-5b-I2V@transformer/diffusion_pytorch_model-00001-of-00003.safetensors
+        - ms://AI-ModelScope/CogVideoX-5b-I2V@transformer/diffusion_pytorch_model-00002-of-00003.safetensors
+        - ms://AI-ModelScope/CogVideoX-5b-I2V@transformer/diffusion_pytorch_model-00003-of-00003.safetensors
+      NUM_ATTENTION_HEADS: 48  # 5b diff
+      ATTENTION_HEAD_DIM: 64
+      IN_CHANNELS: 32  # 5b-I2V diff
+      LATENT_CHANNELS: 16
+      OUT_CHANNELS: 16
+      FLIP_SIN_TO_COS: True
+      FREQ_SHIFT: 0
+      TIME_EMBED_DIM: 512
+      TEXT_EMBED_DIM: 4096
+      NUM_LAYERS: 42  # 5b diff
+      DROPOUT: 0.0
+      ATTENTION_BIAS: True
+      SAMPLE_WIDTH: 90
+      SAMPLE_HEIGHT: 60
+      SAMPLE_FRAMES: 49
+      PATCH_SIZE: 2
+      TEMPORAL_COMPRESSION_RATIO: 4
+      MAX_TEXT_SEQ_LENGTH: 226
+      ACTIVATION_FN: "gelu-approximate"
+      TIMESTEP_ACTIVATION_FN: "silu"
+      NORM_ELEMENTWISE_AFFINE: True
+      NORM_EPS: 1e-5
+      SPATIAL_INTERPOLATION_SCALE: 1.875
+      TEMPORAL_INTERPOLATION_SCALE: 1.0
+      USE_ROTARY_POSITIONAL_EMBEDDINGS: True # 5b diff
+      USE_LEARNED_POSITIONAL_EMBEDDINGS: True  # 5b-I2V diff
+      GRADIENT_CHECKPOINTING: True
+    #
+    FIRST_STAGE_MODEL:
+      NAME: AutoencoderKLCogVideoX
+      DTYPE: bfloat16
+      PRETRAINED_MODEL: ms://AI-ModelScope/CogVideoX-5b-I2V@vae/diffusion_pytorch_model.safetensors # 5b diff
+      SAMPLE_HEIGHT: 480
+      SAMPLE_WIDTH: 720
+      USE_QUANT_CONV: False
+      USE_POST_QUANT_CONV: False
+      USE_SLICING: True
+      USE_TILING: True
+      GRADIENT_CHECKPOINTING: True
+      ENCODER:
+        NAME: CogVideoXEncoder3D
+        IN_CHANNELS: 3
+        OUT_CHANNELS: 16
+        UP_BLOCK_TYPES: [ "CogVideoXDownBlock3D", "CogVideoXDownBlock3D", "CogVideoXDownBlock3D", "CogVideoXDownBlock3D" ]
+        BLOCK_OUT_CHANNELS: [ 128, 256, 256, 512 ]
+        LAYERS_PER_BLOCK: 3
+        ACT_FN: "silu"
+        NORM_EPS: 1e-6
+        NORM_NUM_GROUPS: 32
+        DROPOUT: 0.0
+        PAD_MODE: "first"
+        TEMPORAL_COMPRESSION_RATIO: 4
+        GRADIENT_CHECKPOINTING: True
+      DECODER:
+        NAME: CogVideoXDecoder3D
+        IN_CHANNELS: 16
+        OUT_CHANNELS: 3
+        UP_BLOCK_TYPES: [ "CogVideoXUpBlock3D", "CogVideoXUpBlock3D", "CogVideoXUpBlock3D", "CogVideoXUpBlock3D" ]
+        BLOCK_OUT_CHANNELS: [ 128, 256, 256, 512 ]
+        LAYERS_PER_BLOCK: 3
+        ACT_FN: "silu"
+        NORM_EPS: 1e-6
+        NORM_NUM_GROUPS: 32
+        DROPOUT: 0.0
+        PAD_MODE: "first"
+        TEMPORAL_COMPRESSION_RATIO: 4
+        GRADIENT_CHECKPOINTING: True
+    #
+    COND_STAGE_MODEL:
+      NAME: T5EmbedderHF
+      PRETRAINED_MODEL: ms://AI-ModelScope/t5-v1_1-xxl
+      TOKENIZER_PATH: ms://AI-ModelScope/t5-v1_1-xxl
+      LENGTH: 226
+      CLEAN:
+      USE_GRAD: False
+    #
+    LOSS:
+      NAME: ReconstructLoss
+      LOSS_TYPE: l2
+  #
+  SAMPLE_ARGS:
+    SAMPLER: ddim
+    SAMPLE_STEPS: 50
+    SEED: 42
+    GUIDE_SCALE: 6.0
+    GUIDE_RESCALE: 0.0
+    NUM_FRAMES: 49
+  #
+  OPTIMIZER:
+    NAME: Adam
+    LEARNING_RATE: 1e-3
+    BETAS: [ 0.9, 0.95 ]
+    EPS: 1e-8
+    WEIGHT_DECAY: 0.0
+    AMSGRAD: False
+  #
+#  LR_SCHEDULER:
+#    NAME: StepAnnealingLR
+#    WARMUP_STEPS: 200
+#    TOTAL_STEPS: 2000
+#    DECAY_MODE: 'cosine'
+  #
+  TRAIN_DATA:
+    NAME: VideoGenDataset
+    MODE: train
+    PIN_MEMORY: True
+    BATCH_SIZE: 1
+    NUM_WORKERS: 0
+    PROMPT_PREFIX: 'DISNEY '
+    DATA_TYPE: 'i2v'
+    SAMPLER:
+      NAME: MixtureOfSamplers
+      SUB_SAMPLERS:
+        - NAME: MultiLevelBatchSampler
+          PROB: 1.0
+          FIELDS: [ "video_path", "prompt" ]
+          DELIMITER: '#;#'
+          PATH_PREFIX: cache/datasets/Disney-VideoGeneration-Dataset/
+          INDEX_FILE: cache/datasets/Disney-VideoGeneration-Dataset/index.jsonl
+    TRANSFORMS:
+      - NAME: Select
+        KEYS: [ "video", "image", "prompt" ]
+        META_KEYS: [ ]
+  #
+#  EVAL_DATA:
+#    NAME: Text2ImageDataset
+#    MODE: eval
+#    PROMPT_FILE:
+#    PROMPT_DATA: [ "A cat running.#;#asset/images/edit_tuner/cat_512.jpg" ]
+#    FIELDS: [ "prompt", "img_path" ]
+#    DELIMITER: '#;#'
+#    PROMPT_PREFIX: ''
+#    PIN_MEMORY: True
+#    BATCH_SIZE: 1
+#    USE_NUM: 8
+#    NUM_WORKERS: 0
+#    IMAGE_SIZE: [ 480, 720 ]
+#    TRANSFORMS:
+#      - NAME: LoadImageFromFileList
+#        FILE_KEYS: [ 'img_path' ]
+#        RGB_ORDER: RGB
+#        BACKEND: pillow
+#      - NAME: FlexibleResize
+#        INTERPOLATION: bilinear
+#        SIZE: [ 480, 720 ]
+#        INPUT_KEY: [ 'img' ]
+#        OUTPUT_KEY: [ 'img' ]
+#        BACKEND: pillow
+#      - NAME: FlexibleCenterCrop
+#        SIZE: [ 480, 720 ]
+#        INPUT_KEY: [ 'img' ]
+#        OUTPUT_KEY: [ 'img' ]
+#        BACKEND: pillow
+#      - NAME: ImageToTensor
+#        INPUT_KEY: [ 'img' ]
+#        OUTPUT_KEY: [ 'img' ]
+#        BACKEND: pillow
+#      - NAME: Normalize
+#        MEAN: [ 0.5,  0.5,  0.5 ]
+#        STD: [ 0.5,  0.5,  0.5 ]
+#        INPUT_KEY: [ 'img' ]
+#        OUTPUT_KEY: [ 'image' ]
+#        BACKEND: torchvision
+#      - NAME: Select
+#        KEYS: [ 'image', 'prompt' ]
+#        META_KEYS: [ 'image_size' ]
+  #
+  TRAIN_HOOKS:
+    - NAME: ProbeDataHook
+      PROB_INTERVAL: 100
+      PRIORITY: 0
+    - NAME: BackwardHook
+      PRIORITY: 10
+    - NAME: LogHook
+      LOG_INTERVAL: 10
+      PRIORITY: 20
+    - NAME: CheckpointHook
+      INTERVAL: 1000
+      PRIORITY: 40
+  #
+#  EVAL_HOOKS:
+#    - NAME: ProbeDataHook
+#      PROB_INTERVAL: 100
+#      PRIORITY: 0
@@ -0,0 +1,273 @@
+ENV:
+  BACKEND: nccl
+  SEED: 42
+  TENSOR_PARALLEL_SIZE: 1
+  PIPELINE_PARALLEL_SIZE: 1
+  SYS_ENVS:
+    TORCH_CUDNN_V8_API_ENABLED: '1'
+    TOKENIZERS_PARALLELISM: 'false'
+    TF_CPP_MIN_LOG_LEVEL: '3'
+    PYTORCH_CUDA_ALLOC_CONF: 'expandable_segments:True'
+#
+SOLVER:
+  NAME: LatentDiffusionVideoSolver
+  MAX_STEPS: 2000
+  USE_AMP: True
+  DTYPE: bfloat16
+  USE_FAIRSCALE: False
+  USE_FSDP: True
+  LOAD_MODEL_ONLY: False
+  ENABLE_GRADSCALER: False
+  USE_SCALER: False
+  RESUME_FROM:
+  WORK_DIR: ./cache/save_data/dit_cogvideox_5b_lora
+  LOG_FILE: std_log.txt
+  EVAL_INTERVAL: 100
+  LOG_TRAIN_NUM: 4
+  FPS: 8
+  SHARDING_STRATEGY: full_shard
+  FSDP_REDUCE_DTYPE: float32
+  FSDP_BUFFER_DTYPE: float32
+  FSDP_SHARD_MODULES: [ 'model', 'cond_stage_model.model']
+  SAVE_MODULES: [ 'model', 'cond_stage_model.model']
+  TRAIN_MODULES: ['model']
+  #
+  FILE_SYSTEM:
+    NAME: "ModelscopeFs"
+    TEMP_DIR: "./cache/cache_data"
+  #
+  TUNER:
+    - NAME: SwiftLoRA
+      R: 64
+      LORA_ALPHA: 64
+      LORA_DROPOUT: 0.0
+      BIAS: "none"
+      TARGET_MODULES: "model.*(.to_k|.to_q|.to_v|.to_out.0)$"
+  #
+  MODEL:
+    NAME: LatentDiffusionCogVideoX
+    PRETRAINED_MODEL:
+    PARAMETERIZATION: v
+    TIMESTEPS: 1000
+    MIN_SNR_GAMMA: 3.0
+    ZERO_TERMINAL_SNR: True
+    SCALE_FACTOR_SPATIAL: 8
+    SCALE_FACTOR_TEMPORAL: 4
+    SCALING_FACTOR_IMAGE: 0.7  # 5b diff
+    IGNORE_KEYS: [ ]
+    DEFAULT_N_PROMPT:
+    USE_EMA: False
+    EVAL_EMA: False
+    DIFFUSION:
+      NAME: BaseDiffusion
+      PREDICTION_TYPE: v
+      NOISE_SCHEDULER:
+        NAME: ScaledLinearScheduler
+        BETA_MIN: 0.00085
+        BETA_MAX: 0.012
+        SNR_SHIFT_SCALE: 1.0  # 5b diff
+        RESCALE_BETAS_ZERO_SNR: True
+      DIFFUSION_SAMPLERS:
+        NAME: DDIMSampler
+        DISCRETIZATION_TYPE: trailing
+        ETA: 0.0
+    #
+    DIFFUSION_MODEL:
+      NAME: CogVideoXTransformer3DModel
+      DTYPE: bfloat16
+      PRETRAINED_MODEL: # 5b diff
+        - ms://AI-ModelScope/CogVideoX-5b@transformer/diffusion_pytorch_model-00001-of-00002.safetensors
+        - ms://AI-ModelScope/CogVideoX-5b@transformer/diffusion_pytorch_model-00002-of-00002.safetensors
+      NUM_ATTENTION_HEADS: 48  # 5b diff
+      ATTENTION_HEAD_DIM: 64
+      IN_CHANNELS: 16
+      OUT_CHANNELS: 16
+      FLIP_SIN_TO_COS: True
+      FREQ_SHIFT: 0
+      TIME_EMBED_DIM: 512
+      TEXT_EMBED_DIM: 4096
+      NUM_LAYERS: 42  # 5b diff
+      DROPOUT: 0.0
+      ATTENTION_BIAS: True
+      SAMPLE_WIDTH: 90
+      SAMPLE_HEIGHT: 60
+      SAMPLE_FRAMES: 49
+      PATCH_SIZE: 2
+      TEMPORAL_COMPRESSION_RATIO: 4
+      MAX_TEXT_SEQ_LENGTH: 226
+      ACTIVATION_FN: "gelu-approximate"
+      TIMESTEP_ACTIVATION_FN: "silu"
+      NORM_ELEMENTWISE_AFFINE: True
+      NORM_EPS: 1e-5
+      SPATIAL_INTERPOLATION_SCALE: 1.875
+      TEMPORAL_INTERPOLATION_SCALE: 1.0
+      USE_ROTARY_POSITIONAL_EMBEDDINGS: True # 5b diff
+      USE_LEARNED_POSITIONAL_EMBEDDINGS: False
+      GRADIENT_CHECKPOINTING: True
+    #
+    FIRST_STAGE_MODEL:
+      NAME: AutoencoderKLCogVideoX
+      DTYPE: bfloat16
+      PRETRAINED_MODEL: ms://AI-ModelScope/CogVideoX-5b@vae/diffusion_pytorch_model.safetensors # 5b diff
+      SAMPLE_HEIGHT: 480
+      SAMPLE_WIDTH: 720
+      USE_QUANT_CONV: False
+      USE_POST_QUANT_CONV: False
+      USE_SLICING: True
+      USE_TILING: True
+      GRADIENT_CHECKPOINTING: True
+      ENCODER:
+        NAME: CogVideoXEncoder3D
+        IN_CHANNELS: 3
+        OUT_CHANNELS: 16
+        UP_BLOCK_TYPES: [ "CogVideoXDownBlock3D", "CogVideoXDownBlock3D", "CogVideoXDownBlock3D", "CogVideoXDownBlock3D" ]
+        BLOCK_OUT_CHANNELS: [ 128, 256, 256, 512 ]
+        LAYERS_PER_BLOCK: 3
+        ACT_FN: "silu"
+        NORM_EPS: 1e-6
+        NORM_NUM_GROUPS: 32
+        DROPOUT: 0.0
+        PAD_MODE: "first"
+        TEMPORAL_COMPRESSION_RATIO: 4
+        GRADIENT_CHECKPOINTING: True
+      DECODER:
+        NAME: CogVideoXDecoder3D
+        IN_CHANNELS: 16
+        OUT_CHANNELS: 3
+        UP_BLOCK_TYPES: [ "CogVideoXUpBlock3D", "CogVideoXUpBlock3D", "CogVideoXUpBlock3D", "CogVideoXUpBlock3D" ]
+        BLOCK_OUT_CHANNELS: [ 128, 256, 256, 512 ]
+        LAYERS_PER_BLOCK: 3
+        ACT_FN: "silu"
+        NORM_EPS: 1e-6
+        NORM_NUM_GROUPS: 32
+        DROPOUT: 0.0
+        PAD_MODE: "first"
+        TEMPORAL_COMPRESSION_RATIO: 4
+        GRADIENT_CHECKPOINTING: True
+    #
+    COND_STAGE_MODEL:
+      NAME: T5EmbedderHF
+      PRETRAINED_MODEL: ms://AI-ModelScope/t5-v1_1-xxl
+      TOKENIZER_PATH: ms://AI-ModelScope/t5-v1_1-xxl
+      LENGTH: 226
+      CLEAN:
+      USE_GRAD: False
+    #
+    LOSS:
+      NAME: ReconstructLoss
+      LOSS_TYPE: l2
+  #
+  SAMPLE_ARGS:
+    SAMPLER: ddim
+    SAMPLE_STEPS: 50
+    SEED: 42
+    GUIDE_SCALE: 6.0
+    GUIDE_RESCALE: 0.0
+    NUM_FRAMES: 49
+  #
+  OPTIMIZER:
+    NAME: Adam
+    LEARNING_RATE: 1e-3
+    BETAS: [ 0.9, 0.95 ]
+    EPS: 1e-8
+    WEIGHT_DECAY: 0.0
+    AMSGRAD: False
+  #
+#  LR_SCHEDULER:
+#    NAME: StepAnnealingLR
+#    WARMUP_STEPS: 200
+#    TOTAL_STEPS: 2000
+#    DECAY_MODE: 'cosine'
+  #
+  TRAIN_DATA:
+    NAME: VideoGenDatasetOTF
+    MODE: train
+    PIN_MEMORY: True
+    BATCH_SIZE: 1
+    NUM_WORKERS: 4
+    PROMPT_PREFIX: 'DISNEY '
+    DELIMITER: '#;#'
+    FIELDS: [ 'video_path', 'prompt' ]
+    PATH_PREFIX: cache/datasets/Disney-VideoGeneration-Dataset/
+    DATA_FILE: cache/datasets/Disney-VideoGeneration-Dataset/index.jsonl
+    SAMPLER:
+      NAME: LoopSampler
+    TRANSFORMS:
+      - NAME: Select
+        KEYS: [ 'video', 'video_latent', "prompt" ]
+        META_KEYS: [ ]
+    MODEL:
+      NAME: AutoencoderKLCogVideoX
+      DTYPE: bfloat16
+      PRETRAINED_MODEL: ms://AI-ModelScope/CogVideoX-5b@vae/diffusion_pytorch_model.safetensors
+      SAMPLE_HEIGHT: 480
+      SAMPLE_WIDTH: 720
+      USE_QUANT_CONV: False
+      USE_POST_QUANT_CONV: False
+      USE_SLICING: True
+      USE_TILING: True
+      GRADIENT_CHECKPOINTING: True
+      ENCODER:
+        NAME: CogVideoXEncoder3D
+        IN_CHANNELS: 3
+        OUT_CHANNELS: 16
+        UP_BLOCK_TYPES: [ "CogVideoXDownBlock3D", "CogVideoXDownBlock3D", "CogVideoXDownBlock3D", "CogVideoXDownBlock3D" ]
+        BLOCK_OUT_CHANNELS: [ 128, 256, 256, 512 ]
+        LAYERS_PER_BLOCK: 3
+        ACT_FN: "silu"
+        NORM_EPS: 1e-6
+        NORM_NUM_GROUPS: 32
+        DROPOUT: 0.0
+        PAD_MODE: "first"
+        TEMPORAL_COMPRESSION_RATIO: 4
+        GRADIENT_CHECKPOINTING: True
+      DECODER:
+        NAME: CogVideoXDecoder3D
+        IN_CHANNELS: 16
+        OUT_CHANNELS: 3
+        UP_BLOCK_TYPES: [ "CogVideoXUpBlock3D", "CogVideoXUpBlock3D", "CogVideoXUpBlock3D", "CogVideoXUpBlock3D" ]
+        BLOCK_OUT_CHANNELS: [ 128, 256, 256, 512 ]
+        LAYERS_PER_BLOCK: 3
+        ACT_FN: "silu"
+        NORM_EPS: 1e-6
+        NORM_NUM_GROUPS: 32
+        DROPOUT: 0.0
+        PAD_MODE: "first"
+        TEMPORAL_COMPRESSION_RATIO: 4
+        GRADIENT_CHECKPOINTING: True
+  #
+  EVAL_DATA:
+    NAME: Text2ImageDataset
+    MODE: eval
+    PROMPT_FILE:
+    PROMPT_DATA: [ "A girl riding a bike.", "A panda, dressed in a small, red jacket and a tiny hat, sits on a wooden stool in a serene bamboo forest. The panda's fluffy paws strum a miniature acoustic guitar, producing soft, melodic tunes. Nearby, a few other pandas gather, watching curiously and some clapping in rhythm. Sunlight filters through the tall bamboo, casting a gentle glow on the scene. The panda's face is expressive, showing concentration and joy as it plays. The background includes a small, flowing stream and vibrant green foliage, enhancing the peaceful and magical atmosphere of this unique musical performance." ]
+    IMAGE_SIZE: [ 480, 720 ]
+    FIELDS: [ "prompt" ]
+    DELIMITER: '#;#'
+    PROMPT_PREFIX: 'DISNEY '
+    PIN_MEMORY: True
+    BATCH_SIZE: 1
+    USE_NUM: 8
+    NUM_WORKERS: 4
+    TRANSFORMS:
+      - NAME: Select
+        KEYS: [ 'index', 'prompt' ]
+        META_KEYS: [ 'image_size' ]
+  #
+  TRAIN_HOOKS:
+    - NAME: ProbeDataHook
+      PROB_INTERVAL: 100
+      PRIORITY: 0
+    - NAME: BackwardHook
+      PRIORITY: 10
+    - NAME: LogHook
+      LOG_INTERVAL: 10
+      PRIORITY: 20
+    - NAME: CheckpointHook
+      INTERVAL: 1000
+      PRIORITY: 40
+  #
+  EVAL_HOOKS:
+    - NAME: ProbeDataHook
+      PROB_INTERVAL: 100
+      PRIORITY: 0
@@ -0,0 +1,246 @@
+ENV:
+  BACKEND: nccl
+  SEED: 166666
+SOLVER:
+  NAME: LatentDiffusionSolver
+  MAX_STEPS: 100000
+  USE_AMP: True
+  DTYPE: bfloat16
+  USE_FAIRSCALE: False
+  USE_FSDP: True
+  LOAD_MODEL_ONLY: False
+  ENABLE_GRADSCALER: False
+  USE_SCALER: False
+  RESUME_FROM:
+  WORK_DIR: ./cache/save_data/dit_flux_dev_1024_lora
+  LOG_FILE: std_log.txt
+  EVAL_INTERVAL: 100
+  LOG_TRAIN_NUM: 16
+  FSDP_REDUCE_DTYPE: float32
+  FSDP_BUFFER_DTYPE: float32
+  FSDP_SHARD_MODULES: [ 'model', 'cond_stage_model.t5_model' ] #
+  SAVE_MODULES: [ 'model'] #
+  TRAIN_MODULES: ['model']
+  #
+  FILE_SYSTEM:
+    NAME: "ModelscopeFs"
+    TEMP_DIR: "./cache/cache_data"
+  #
+  FREEZE:
+  TUNER:
+    - NAME: SwiftLoRA
+      R: 4
+      LORA_ALPHA: 4
+      LORA_DROPOUT: 0.0
+      BIAS: "none"
+      TARGET_MODULES: "(model.double_blocks.*(.qkv|.proj|.img_mod.lin|.txt_mod.lin))|(model.single_blocks.*(.linear1|.linear2|.modulation.lin))$"
+  ##
+  MODEL:
+    NAME: LatentDiffusionFlux
+    PARAMETERIZATION: rf
+    TIMESTEPS: 1000
+    MIN_SNR_GAMMA:
+    ZERO_TERMINAL_SNR: False
+    PRETRAINED_MODEL:
+    IGNORE_KEYS: [ ]
+    DEFAULT_N_PROMPT:
+    USE_EMA: False
+    EVAL_EMA: False
+    DIFFUSION:
+      NAME: DiffusionFluxRF
+      PREDICTION_TYPE: raw
+      NOISE_SCHEDULER:
+        NAME: FlowMatchSigmaScheduler
+        WEIGHTING_SCHEME: logit_normal
+        SHIFT: 3.0
+        LOGIT_MEAN: 0.0
+        LOGIT_STD: 1.0
+        MODE_SCALE: 1.29
+      SAMPLER_SCHEDULER:
+        NAME: FlowMatchFluxShiftScheduler
+        SHIFT: False
+        SIGMOID_SCALE: 1
+        BASE_SHIFT: 0.5
+        MAX_SHIFT: 1.15
+        #
+    DIFFUSION_MODEL:
+      NAME: Flux
+      PRETRAINED_MODEL: ms://AI-ModelScope/FLUX.1-dev@flux1-dev.safetensors
+      IN_CHANNELS: 64
+      HIDDEN_SIZE: 3072
+      NUM_HEADS: 24
+      AXES_DIM: [ 16, 56, 56 ]
+      THETA: 10000
+      VEC_IN_DIM: 768
+      GUIDANCE_EMBED: True
+      CONTEXT_IN_DIM: 4096
+      MLP_RATIO: 4.0
+      QKV_BIAS: True
+      DEPTH: 19
+      DEPTH_SINGLE_BLOCKS: 38
+      USE_GRAD_CHECKPOINT: True
+
+    #
+    FIRST_STAGE_MODEL:
+      NAME: AutoencoderKLFlux
+      EMBED_DIM: 16
+      PRETRAINED_MODEL: ms://AI-ModelScope/FLUX.1-dev@ae.safetensors
+      IGNORE_KEYS: [ ]
+      BATCH_SIZE: 8
+      USE_CONV: False
+      SCALE_FACTOR: 0.3611
+      SHIFT_FACTOR: 0.1159
+      #
+      ENCODER:
+        NAME: Encoder
+        USE_CHECKPOINT: True
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 16
+        DOUBLE_Z: True
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+      #
+      DECODER:
+        NAME: Decoder
+        USE_CHECKPOINT: True
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 16
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+        GIVE_PRE_END: False
+        TANH_OUT: False
+    #
+    COND_STAGE_MODEL:
+      NAME: T5PlusClipFluxEmbedder
+      T5_MODEL:
+        NAME: HFEmbedder
+        HF_MODEL_CLS: T5EncoderModel
+        MODEL_PATH: ms://AI-ModelScope/FLUX.1-dev@text_encoder_2/
+        HF_TOKENIZER_CLS: T5Tokenizer
+        TOKENIZER_PATH: ms://AI-ModelScope/FLUX.1-dev@tokenizer_2/
+        MAX_LENGTH: 512
+        OUTPUT_KEY: last_hidden_state
+        D_TYPE: bfloat16
+        BATCH_INFER: False
+        CLEAN: whitespace
+      CLIP_MODEL:
+        NAME: HFEmbedder
+        HF_MODEL_CLS: CLIPTextModel
+        MODEL_PATH: ms://AI-ModelScope/FLUX.1-dev@text_encoder/
+        HF_TOKENIZER_CLS: CLIPTokenizer
+        TOKENIZER_PATH: ms://AI-ModelScope/FLUX.1-dev@tokenizer/
+        MAX_LENGTH: 77
+        OUTPUT_KEY: pooler_output
+        D_TYPE: bfloat16
+        BATCH_INFER: True
+        CLEAN: whitespace
+        USE_GRAD_CHECKPOINT: True
+  #
+  SAMPLE_ARGS:
+    SAMPLE_STEPS: 50
+    SAMPLER: flow_euler
+    SEED: 2024
+    IMAGE_SIZE: [ 1024, 1024 ]
+    GUIDE_SCALE: 3.5
+  #
+  OPTIMIZER:
+    NAME: AdamW
+    LEARNING_RATE: 4e-4
+    BETAS: [ 0.9, 0.999 ]
+    EPS: 1e-8
+    WEIGHT_DECAY: 1e-2
+    AMSGRAD: False
+  #
+  TRAIN_DATA:
+    NAME: ImageTextPairMSDataset
+    MODE: train
+    MS_DATASET_NAME: style_custom_dataset
+    MS_DATASET_NAMESPACE: damo
+    MS_DATASET_SUBNAME: 3D
+    PROMPT_PREFIX: ""
+    MS_DATASET_SPLIT: train
+    MS_REMAP_KEYS: { 'Image:FILE': 'Target:FILE' }
+    REPLACE_STYLE: False
+    PIN_MEMORY: True
+    BATCH_SIZE: 1
+    NUM_WORKERS: 4
+    SAMPLER:
+      NAME: LoopSampler
+    TRANSFORMS:
+      - NAME: LoadImageFromFile
+        RGB_ORDER: RGB
+        BACKEND: pillow
+      - NAME: FlexibleResize
+        INTERPOLATION: bilinear
+        SIZE: [ 1024, 1024 ]
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'img' ]
+        BACKEND: pillow
+      - NAME: FlexibleCenterCrop
+        SIZE: [ 1024, 1024 ]
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'img' ]
+        BACKEND: pillow
+      - NAME: ImageToTensor
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'img' ]
+        BACKEND: pillow
+      - NAME: Normalize
+        MEAN: [ 0.5,  0.5,  0.5 ]
+        STD: [ 0.5,  0.5,  0.5 ]
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'image' ]
+        BACKEND: torchvision
+      - NAME: Select
+        KEYS: [ 'image', 'prompt' ]
+        META_KEYS: [ 'data_key' ]
+  #
+  EVAL_DATA:
+    NAME: Text2ImageDataset
+    MODE: eval
+    PROMPT_FILE:
+    PROMPT_DATA: [ "a boy wearing a jacket", "a dog running on the lawn" ]
+    IMAGE_SIZE: [ 1024, 1024 ]
+    FIELDS: [ "prompt" ]
+    DELIMITER: '#;#'
+    PROMPT_PREFIX: ''
+    PIN_MEMORY: True
+    BATCH_SIZE: 2
+    NUM_WORKERS: 4
+    TRANSFORMS:
+      - NAME: Select
+        KEYS: [ 'index', 'prompt' ]
+        META_KEYS: [ 'image_size' ]
+  #
+  TRAIN_HOOKS:
+    - NAME: ProbeDataHook
+      PROB_INTERVAL: 100
+      PRIORITY: 0
+    - NAME: BackwardHook
+#      GRADIENT_CLIP: 1.0
+      PRIORITY: 10
+    - NAME: LogHook
+      LOG_INTERVAL: 10
+    -
+      NAME: TensorboardLogHook
+    -
+      NAME: CheckpointHook
+      INTERVAL: 10000
+      PRIORITY: 200
+      SAVE_LAST: True
+      SAVE_NAME_PREFIX: 'step'
+      DISABLE_SNAPSHOT: True
+  EVAL_HOOKS:
+    - NAME: ProbeDataHook
+      PROB_INTERVAL: 100
+      PRIORITY: 0
@@ -0,0 +1,267 @@
+ENV:
+  BACKEND: nccl
+  SEED: 166666
+SOLVER:
+  NAME: LatentDiffusionSolver
+  MAX_STEPS: 100000
+  USE_AMP: True
+  DTYPE: bfloat16
+  USE_FAIRSCALE: False
+  USE_FSDP: True
+  LOAD_MODEL_ONLY: False
+  ENABLE_GRADSCALER: False
+  USE_SCALER: False
+  RESUME_FROM:
+  WORK_DIR: ./cache/save_data/dit_flux_schnell_1024_lora
+  LOG_FILE: std_log.txt
+  EVAL_INTERVAL: 100
+  LOG_TRAIN_NUM: 16
+  FSDP_REDUCE_DTYPE: float32
+  FSDP_BUFFER_DTYPE: float32
+  FSDP_SHARD_MODULES: [ 'model', 'cond_stage_model.t5_model' ] #
+  SAVE_MODULES: [ 'model']
+  TRAIN_MODULES: ['model']
+  #
+  FILE_SYSTEM:
+    NAME: "ModelscopeFs"
+    TEMP_DIR: "./cache/cache_data"
+  #
+  FREEZE:
+  TUNER:
+    - NAME: SwiftLoRA
+      R: 4
+      LORA_ALPHA: 4
+      LORA_DROPOUT: 0.0
+      BIAS: "none"
+      TARGET_MODULES: "(model.double_blocks.*(.qkv|.proj|.img_mod.lin|.txt_mod.lin))|(model.single_blocks.*(.linear1|.linear2|.modulation.lin))$"
+  ##
+  MODEL:
+    NAME: LatentDiffusionFlux
+    PARAMETERIZATION: rf
+    TIMESTEPS: 1000
+    MIN_SNR_GAMMA:
+    ZERO_TERMINAL_SNR: False
+    PRETRAINED_MODEL:
+    IGNORE_KEYS: [ ]
+    DEFAULT_N_PROMPT:
+    USE_EMA: False
+    EVAL_EMA: False
+    DIFFUSION:
+      NAME: DiffusionFluxRF
+      PREDICTION_TYPE: raw
+      NOISE_SCHEDULER:
+        NAME: FlowMatchSigmaScheduler
+        # WEIGHTING_SCHEME DESCRIPTION: The weighting scheme for sampling timesteps, choose from ['sigma_sqrt', 'logit_normal', 'mode', 'cosmap', 'none']. TYPE: str default: 'logit_normal'
+        WEIGHTING_SCHEME: logit_normal
+        SHIFT: 3.0
+        # LOGIT_MEAN DESCRIPTION: The mean of the logit distribution for sampling timesteps. TYPE: float default: 0.0
+        LOGIT_MEAN: 0.0
+        # LOGIT_STD DESCRIPTION: The standard deviation of the logit distribution for sampling timesteps. TYPE: float default: 1.0
+        LOGIT_STD: 1.0
+        # MODE_SCALE DESCRIPTION: The scale factor for the mode of the logit distribution for sampling timesteps. TYPE: float default: 1.29
+        MODE_SCALE: 1.29
+      SAMPLER_SCHEDULER:
+        # NAME DESCRIPTION:  TYPE:  default: 'FlowMatchFluxShiftScheduler'
+        NAME: FlowMatchFluxShiftScheduler
+        # SHIFT DESCRIPTION: Use timestamp shift or not, default is True. TYPE: bool default: True
+        SHIFT: False
+        # SIGMOID_SCALE DESCRIPTION: The scale of sigmoid function for sampling timesteps. TYPE: int default: 1
+        SIGMOID_SCALE: 1
+        # BASE_SHIFT DESCRIPTION: The base shift factor for the timestamp. TYPE: float default: 0.5
+        BASE_SHIFT: 0.5
+        # MAX_SHIFT DESCRIPTION: The max shift factor for the timestamp. TYPE: float default: 1.15
+        MAX_SHIFT: 1.15
+        #
+    DIFFUSION_MODEL:
+      # NAME DESCRIPTION:  TYPE:  default: 'Flux'
+      NAME: Flux
+      PRETRAINED_MODEL: ms://AI-ModelScope/FLUX.1-schnell@flux1-schnell.safetensors
+      # IN_CHANNELS DESCRIPTION: model's input channels. TYPE: int default: 64
+      IN_CHANNELS: 64
+      # HIDDEN_SIZE DESCRIPTION: model's hidden size. TYPE: int default: 1024
+      HIDDEN_SIZE: 3072
+      # NUM_HEADS DESCRIPTION: number of heads in the transformer. TYPE: int default: 16
+      NUM_HEADS: 24
+      # AXES_DIM DESCRIPTION: dimensions of the axes of the positional encoding. TYPE: list default: [16, 56, 56]
+      AXES_DIM: [ 16, 56, 56 ]
+      # THETA DESCRIPTION: theta for positional encoding. TYPE: int default: 10000
+      THETA: 10000
+      # VEC_IN_DIM DESCRIPTION: dimension of the vector input. TYPE: int default: 768
+      VEC_IN_DIM: 768
+      # GUIDANCE_EMBED DESCRIPTION: whether to use guidance embedding. TYPE: bool default: False
+      GUIDANCE_EMBED: False
+      # CONTEXT_IN_DIM DESCRIPTION: dimension of the context input. TYPE: int default: 4096
+      CONTEXT_IN_DIM: 4096
+      # MLP_RATIO DESCRIPTION: ratio of mlp hidden size to hidden size. TYPE: float default: 4.0
+      MLP_RATIO: 4.0
+      # QKV_BIAS DESCRIPTION: whether to use bias in qkv projection. TYPE: bool default: True
+      QKV_BIAS: True
+      # DEPTH DESCRIPTION: number of transformer blocks. TYPE: int default: 19
+      DEPTH: 19
+      # DEPTH_SINGLE_BLOCKS DESCRIPTION: number of transformer blocks in the single stream block. TYPE: int default: 38
+      DEPTH_SINGLE_BLOCKS: 38
+      USE_GRAD_CHECKPOINT: True
+
+    #
+    FIRST_STAGE_MODEL:
+      NAME: AutoencoderKLFlux
+      EMBED_DIM: 16
+      PRETRAINED_MODEL: ms://AI-ModelScope/FLUX.1-schnell@ae.safetensors
+      IGNORE_KEYS: [ ]
+      BATCH_SIZE: 8
+      USE_CONV: False
+      SCALE_FACTOR: 0.3611
+      SHIFT_FACTOR: 0.1159
+      #
+      ENCODER:
+        NAME: Encoder
+        USE_CHECKPOINT: True
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 16
+        DOUBLE_Z: True
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+      #
+      DECODER:
+        NAME: Decoder
+        USE_CHECKPOINT: True
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 16
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+        GIVE_PRE_END: False
+        TANH_OUT: False
+    #
+    COND_STAGE_MODEL:
+      NAME: T5PlusClipFluxEmbedder
+      T5_MODEL:
+        NAME: HFEmbedder
+        HF_MODEL_CLS: T5EncoderModel
+        MODEL_PATH: ms://AI-ModelScope/FLUX.1-schnell@text_encoder_2/
+        HF_TOKENIZER_CLS: T5Tokenizer
+        TOKENIZER_PATH: ms://AI-ModelScope/FLUX.1-schnell@tokenizer_2/
+        MAX_LENGTH: 256
+        OUTPUT_KEY: last_hidden_state
+        D_TYPE: bfloat16
+        BATCH_INFER: False
+        CLEAN: whitespace
+      CLIP_MODEL:
+        NAME: HFEmbedder
+        HF_MODEL_CLS: CLIPTextModel
+        MODEL_PATH: ms://AI-ModelScope/FLUX.1-schnell@text_encoder/
+        HF_TOKENIZER_CLS: CLIPTokenizer
+        TOKENIZER_PATH: ms://AI-ModelScope/FLUX.1-schnell@tokenizer/
+        MAX_LENGTH: 77
+        OUTPUT_KEY: pooler_output
+        D_TYPE: bfloat16
+        BATCH_INFER: True
+        CLEAN: whitespace
+  #
+  SAMPLE_ARGS:
+    SAMPLE_STEPS: 4
+    SAMPLER: flow_euler
+    SEED: 2024
+    IMAGE_SIZE: [ 1024, 1024 ]
+    GUIDE_SCALE: 3.5
+  #
+  OPTIMIZER:
+    NAME: AdamW
+    LEARNING_RATE: 4e-4
+    BETAS: [ 0.9, 0.999 ]
+    EPS: 1e-8
+    WEIGHT_DECAY: 1e-2
+    AMSGRAD: False
+  #
+  TRAIN_DATA:
+    NAME: ImageTextPairMSDataset
+    MODE: train
+    MS_DATASET_NAME: style_custom_dataset
+    MS_DATASET_NAMESPACE: damo
+    MS_DATASET_SUBNAME: 3D
+    PROMPT_PREFIX: ""
+    MS_DATASET_SPLIT: train
+    MS_REMAP_KEYS: { 'Image:FILE': 'Target:FILE' }
+    REPLACE_STYLE: False
+    PIN_MEMORY: True
+    BATCH_SIZE: 1
+    NUM_WORKERS: 4
+    SAMPLER:
+      NAME: LoopSampler
+    TRANSFORMS:
+      - NAME: LoadImageFromFile
+        RGB_ORDER: RGB
+        BACKEND: pillow
+      - NAME: FlexibleResize
+        INTERPOLATION: bilinear
+        SIZE: [ 1024, 1024 ]
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'img' ]
+        BACKEND: pillow
+      - NAME: FlexibleCenterCrop
+        SIZE: [ 1024, 1024 ]
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'img' ]
+        BACKEND: pillow
+      - NAME: ImageToTensor
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'img' ]
+        BACKEND: pillow
+      - NAME: Normalize
+        MEAN: [ 0.5,  0.5,  0.5 ]
+        STD: [ 0.5,  0.5,  0.5 ]
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'image' ]
+        BACKEND: torchvision
+      - NAME: Select
+        KEYS: [ 'image', 'prompt' ]
+        META_KEYS: [ 'data_key' ]
+  #
+  EVAL_DATA:
+    NAME: Text2ImageDataset
+    MODE: eval
+    PROMPT_FILE:
+    PROMPT_DATA: [ "a boy wearing a jacket", "a dog running on the lawn" ]
+    IMAGE_SIZE: [ 1024, 1024 ]
+    FIELDS: [ "prompt" ]
+    DELIMITER: '#;#'
+    PROMPT_PREFIX: ''
+    PIN_MEMORY: True
+    BATCH_SIZE: 2
+    NUM_WORKERS: 4
+    TRANSFORMS:
+      - NAME: Select
+        KEYS: [ 'index', 'prompt' ]
+        META_KEYS: [ 'image_size' ]
+  #
+  TRAIN_HOOKS:
+    - NAME: ProbeDataHook
+      PROB_INTERVAL: 100
+      PRIORITY: 0
+    - NAME: BackwardHook
+#      GRADIENT_CLIP: 1.0
+      PRIORITY: 10
+    - NAME: LogHook
+      LOG_INTERVAL: 10
+    -
+      NAME: TensorboardLogHook
+    -
+      NAME: CheckpointHook
+      INTERVAL: 10000
+      PRIORITY: 200
+      SAVE_LAST: True
+      SAVE_NAME_PREFIX: 'step'
+      DISABLE_SNAPSHOT: True
+  EVAL_HOOKS:
+    - NAME: ProbeDataHook
+      PROB_INTERVAL: 100
+      PRIORITY: 0
@@ -0,0 +1,223 @@
+ENV:
+  BACKEND: nccl
+#
+SOLVER:
+  NAME: LatentDiffusionSolver
+  RESUME_FROM:
+  LOAD_MODEL_ONLY: True
+  USE_FSDP: False
+  SHARDING_STRATEGY:
+  USE_AMP: True
+  DTYPE: float16
+  CHANNELS_LAST: True
+  MAX_STEPS: 1000
+  MAX_EPOCHS: -1
+  NUM_FOLDS: 1
+  ACCU_STEP: 1
+  EVAL_INTERVAL: 100
+  RESCALE_LR: False
+  #
+  WORK_DIR: ./cache/save_data/dit_pixart_alpha_1024_lora
+  LOG_FILE: std_log.txt
+  #
+  FILE_SYSTEM:
+    NAME: "ModelscopeFs"
+    TEMP_DIR: "./cache/cache_data"
+  #
+  FREEZE:
+  #
+  TUNER:
+    - NAME: SwiftLoRA
+      R: 128
+      LORA_ALPHA: 128
+      LORA_DROPOUT: 0.0
+      BIAS: "none"
+      TARGET_MODULES: "model.*(.q|.k|.v|.o|mlp.fc1|mlp.fc2)$"
+  #
+  MODEL:
+    NAME: LatentDiffusionPixart
+    PARAMETERIZATION: eps
+    TIMESTEPS: 1000
+    MIN_SNR_GAMMA:
+    ZERO_TERMINAL_SNR: False
+    PRETRAINED_MODEL:
+    IGNORE_KEYS: [ ]
+    SCALE_FACTOR: 0.18215
+    SIZE_FACTOR: 8
+    DECODER_BIAS: 0.5
+    DEFAULT_N_PROMPT:
+    SCHEDULE_ARGS:
+      "NAME": "linear"
+      "BETA_MIN": 0.0001
+      "BETA_MAX": 0.02
+    USE_EMA: False
+    LOAD_REFINER: False
+    #
+    DIFFUSION_MODEL:
+      NAME: PixArt
+      PRETRAINED_MODEL: ms://AI-ModelScope/PixArt-alpha@PixArt-XL-2-1024-MS.pth
+      INPUT_SIZE: 128
+      PATCH_SIZE: 2
+      IN_CHANNELS: 4
+      HIDDEN_SIZE: 1152
+      DEPTH: 28
+      NUM_HEADS: 16
+      MLP_RATIO: 4.0
+      CLASS_DROPOUT_PROB: 0.1
+      PRED_SIGMA: True
+      DROP_PATH: 0.0
+      WINDOW_DIZE: 0
+      USE_REL_POS: False
+      CAPTION_CHANNELS: 4096
+      LEWEI_SCALE: 2
+      MODEL_MAX_LENGTH: 120
+    #
+    FIRST_STAGE_MODEL:
+      NAME: AutoencoderKL
+      PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-2-base@512-base-ema.safetensors
+      EMBED_DIM: 4
+      IGNORE_KEYS: [ ]
+      BATCH_SIZE: 1
+      #
+      ENCODER:
+        NAME: Encoder
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 4
+        DOUBLE_Z: True
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+      #
+      DECODER:
+        NAME: Decoder
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 4
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+        GIVE_PRE_END: False
+        TANH_OUT: False
+    #
+    COND_STAGE_MODEL:
+      NAME: T5EmbedderHF
+      PRETRAINED_MODEL: ms://AI-ModelScope/PixArt-alpha@t5-v1_1-xxl/
+      TOKENIZER_PATH: ms://AI-ModelScope/PixArt-alpha@t5-v1_1-xxl/
+      LENGTH: 120
+      CLEAN: heavy
+      USE_GRAD: False
+    #
+    LOSS:
+      NAME: ReconstructLoss
+      LOSS_TYPE: l2
+  #
+  SAMPLE_ARGS:
+    SAMPLER: ddim
+    SAMPLE_STEPS: 20
+    SEED: 2024
+    GUIDE_SCALE: 4.5
+    GUIDE_RESCALE: 0.5
+    DISCRETIZATION: trailing
+    RUN_TRAIN_N: False
+  #
+  OPTIMIZER:
+    NAME: AdamW
+    LEARNING_RATE: 0.0001
+    BETAS: [ 0.9, 0.999 ]
+    EPS: 1e-8
+    WEIGHT_DECAY: 1e-2
+    AMSGRAD: False
+  #
+  TRAIN_DATA:
+    NAME: ImageTextPairMSDataset
+    MODE: train
+    MS_DATASET_NAME: style_custom_dataset
+    MS_DATASET_NAMESPACE: damo
+    MS_DATASET_SUBNAME: 3D
+    PROMPT_PREFIX: ""
+    MS_DATASET_SPLIT: train
+    MS_REMAP_KEYS: { 'Image:FILE': 'Target:FILE' }
+    REPLACE_STYLE: False
+    PIN_MEMORY: True
+    BATCH_SIZE: 1
+    NUM_WORKERS: 4
+    SAMPLER:
+      NAME: LoopSampler
+    TRANSFORMS:
+      - NAME: LoadImageFromFile
+        RGB_ORDER: RGB
+        BACKEND: pillow
+      - NAME: FlexibleResize
+        INTERPOLATION: bilinear
+        SIZE: [ 1024, 1024 ]
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'img' ]
+        BACKEND: pillow
+      - NAME: FlexibleCenterCrop
+        SIZE: [ 1024, 1024 ]
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'img' ]
+        BACKEND: pillow
+      - NAME: ImageToTensor
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'img' ]
+        BACKEND: pillow
+      - NAME: Normalize
+        MEAN: [ 0.5,  0.5,  0.5 ]
+        STD: [ 0.5,  0.5,  0.5 ]
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'image' ]
+        BACKEND: torchvision
+      - NAME: Select
+        KEYS: [ 'image', 'prompt' ]
+        META_KEYS: [ 'data_key' ]
+  #
+  EVAL_DATA:
+    NAME: Text2ImageDataset
+    MODE: eval
+    PROMPT_FILE:
+    PROMPT_DATA: [ "a boy wearing a jacket", "a dog running on the lawn" ]
+    IMAGE_SIZE: [ 1024, 1024 ]
+    FIELDS: [ "prompt" ]
+    DELIMITER: '#;#'
+    PROMPT_PREFIX: ''
+    PIN_MEMORY: True
+    BATCH_SIZE: 1
+    NUM_WORKERS: 4
+    TRANSFORMS:
+      - NAME: Select
+        KEYS: [ 'index', 'prompt' ]
+        META_KEYS: [ 'image_size' ]
+  #
+  TRAIN_HOOKS:
+    -
+      NAME: BackwardHook
+      PRIORITY: 0
+    -
+      NAME: LogHook
+      LOG_INTERVAL: 10
+      SHOW_GPU_MEM: True
+    -
+      NAME: TensorboardLogHook
+    -
+      NAME: CheckpointHook
+      INTERVAL: 10000
+      PRIORITY: 200
+      SAVE_LAST: True
+      SAVE_NAME_PREFIX: 'step'
+      DISABLE_SNAPSHOT: True
+  #
+  EVAL_HOOKS:
+    -
+      NAME: ProbeDataHook
+      PROB_INTERVAL: 100
+      SAVE_LAST: True
+      SAVE_NAME_PREFIX: 'step'
+      SAVE_PROBE_PREFIX: 'image'
@@ -0,0 +1,233 @@
+ENV:
+  BACKEND: nccl
+#
+SOLVER:
+  NAME: LatentDiffusionSolver
+  RESUME_FROM:
+  LOAD_MODEL_ONLY: True
+  USE_FSDP: False
+  SHARDING_STRATEGY:
+  USE_AMP: True
+  DTYPE: float16
+  CHANNELS_LAST: True
+  MAX_STEPS: 500
+  MAX_EPOCHS: -1
+  NUM_FOLDS: 1
+  ACCU_STEP: 1
+  EVAL_INTERVAL: 50
+  RESCALE_LR: False
+  #
+  WORK_DIR: ./cache/save_data/dit_sd3_1024
+  LOG_FILE: std_log.txt
+  #
+  FILE_SYSTEM:
+    - NAME: "ModelscopeFs"
+      TEMP_DIR: ./cache/cache_data
+  #
+  MODEL:
+    NAME: LatentDiffusionSD3
+    PARAMETERIZATION: rf
+    TIMESTEPS: 1000
+    MIN_SNR_GAMMA:
+    ZERO_TERMINAL_SNR: False
+    PRETRAINED_MODEL:
+    IGNORE_KEYS: [ ]
+    SCALE_FACTOR: 1.5305
+    SHIFT_FACTOR: 0.0609
+    DEFAULT_N_PROMPT:
+    SCHEDULE_ARGS:
+      "NAME": "shifted"
+      "SHIFT": 3
+    USE_EMA: False
+    T_WEIGHT: uniform
+    #
+    DIFFUSION_MODEL:
+      NAME: MMDiT
+      PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium@sd3_medium.safetensors
+      IGNORE_KEYS: '^first_stage_model.'
+      IN_CHANNELS: 16
+      PATCH_SIZE: 2
+      OUT_CHANNELS: 16
+      DEPTH: 24
+      INPUT_SIZE:
+      ADM_IN_CHANNELS: 2048
+      CONTEXT_EMBEDDER_CONFIG: { 'target': 'torch.nn.Linear', 'params': { 'in_features': 4096, 'out_features': 1536 } }
+      NUM_PATCHES: 36864
+      POS_EMBED_MAX_SIZE: 192
+      POS_EMBED_SCALING_FACTOR:
+      USE_CHECKPOINT: True
+    #
+    FIRST_STAGE_MODEL:
+      NAME: AutoencoderKL
+      PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium@sd3_medium.safetensors
+      EMBED_DIM: 16
+      IGNORE_KEYS: '^model.diffusion_model.'
+      BATCH_SIZE: 1
+      USE_CONV: False
+      #
+      ENCODER:
+        NAME: Encoder
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 16
+        DOUBLE_Z: True
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+      #
+      DECODER:
+        NAME: Decoder
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 16
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+        GIVE_PRE_END: False
+        TANH_OUT: False
+    #
+    COND_STAGE_MODEL:
+      NAME: SD3TextEmbedder
+      P_ZERO: 0.0
+      CLIP_L:
+        NAME: FrozenCLIPEmbedder2
+        PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@text_encoder
+        TOKENIZER_PATH: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@tokenizer
+        MAX_LENGTH: 77
+        FREEZE: True
+        LAYER: penultimate
+        RETURN_POOLED: True
+        USE_FINAL_LAYER_NORM: False
+        IS_TRAINABLE: False
+      CLIP_G:
+        NAME: FrozenCLIPEmbedder2
+        PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@text_encoder_2
+        TOKENIZER_PATH: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@tokenizer_2
+        MAX_LENGTH: 77
+        FREEZE: True
+        LAYER: penultimate
+        RETURN_POOLED: True
+        USE_FINAL_LAYER_NORM: False
+        IS_TRAINABLE: False
+      T5_XXL:
+        NAME: T5EmbedderHF
+        PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@text_encoder_3
+        TOKENIZER_PATH: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@tokenizer_3
+        LENGTH: 256
+        CLEAN: whitespace
+        USE_GRAD: False
+        T5_DTYPE: float16
+    #
+    LOSS:
+      NAME: ReconstructLoss
+      LOSS_TYPE: l2
+  #
+  SAMPLE_ARGS:
+    SAMPLER: euler
+    SAMPLE_STEPS: 28
+    SEED: 1749023094
+    GUIDE_SCALE: 5.0
+    GUIDE_RESCALE: 0.0
+    DISCRETIZATION: trailing
+    RUN_TRAIN_N: False
+  #
+  OPTIMIZER:
+    NAME: AdamW
+    LEARNING_RATE: 1e-5
+    BETAS: [ 0.9, 0.999 ]
+    EPS: 1e-8
+    WEIGHT_DECAY: 1e-2
+    AMSGRAD: False
+  #
+  TRAIN_DATA:
+    NAME: ImageTextPairMSDataset
+    MODE: train
+    MS_DATASET_NAME: style_custom_dataset
+    MS_DATASET_NAMESPACE: damo
+    MS_DATASET_SUBNAME: 3D
+    PROMPT_PREFIX: ""
+    MS_DATASET_SPLIT: train
+    MS_REMAP_KEYS: { 'Image:FILE': 'Target:FILE' }
+    REPLACE_STYLE: False
+    PIN_MEMORY: True
+    BATCH_SIZE: 1
+    NUM_WORKERS: 4
+    SAMPLER:
+      NAME: LoopSampler
+    TRANSFORMS:
+      - NAME: LoadImageFromFile
+        RGB_ORDER: RGB
+        BACKEND: pillow
+      - NAME: FlexibleResize
+        INTERPOLATION: bilinear
+        SIZE: [ 1024, 1024 ]
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'img' ]
+        BACKEND: pillow
+      - NAME: FlexibleCenterCrop
+        SIZE: [ 1024, 1024 ]
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'img' ]
+        BACKEND: pillow
+      - NAME: ImageToTensor
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'img' ]
+        BACKEND: pillow
+      - NAME: Normalize
+        MEAN: [ 0.5,  0.5,  0.5 ]
+        STD: [ 0.5,  0.5,  0.5 ]
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'image' ]
+        BACKEND: torchvision
+      - NAME: Select
+        KEYS: [ 'image', 'prompt' ]
+        META_KEYS: [ 'data_key' ]
+  #
+  EVAL_DATA:
+    NAME: Text2ImageDataset
+    MODE: eval
+    PROMPT_FILE:
+    PROMPT_DATA: [ "a cat holds a blackboard that writes \"hello world\"", "a dog running on the lawn" ]
+    IMAGE_SIZE: [ 1024, 1024 ]
+    FIELDS: [ "prompt" ]
+    DELIMITER: '#;#'
+    PROMPT_PREFIX: ''
+    PIN_MEMORY: True
+    BATCH_SIZE: 1
+    NUM_WORKERS: 4
+    TRANSFORMS:
+      - NAME: Select
+        KEYS: [ 'index', 'prompt' ]
+        META_KEYS: [ 'image_size' ]
+  #
+  TRAIN_HOOKS:
+    -
+      NAME: BackwardHook
+      PRIORITY: 10000
+    -
+      NAME: LogHook
+      LOG_INTERVAL: 10
+      SHOW_GPU_MEM: True
+    -
+      NAME: TensorboardLogHook
+    -
+      NAME: CheckpointHook
+      INTERVAL: 10000
+      PRIORITY: 200
+      SAVE_LAST: True
+      SAVE_NAME_PREFIX: 'step'
+      DISABLE_SNAPSHOT: True
+  #
+  EVAL_HOOKS:
+    -
+      NAME: ProbeDataHook
+      PROB_INTERVAL: 50
+      SAVE_LAST: True
+      SAVE_NAME_PREFIX: 'step'
+      SAVE_PROBE_PREFIX: 'image'
@@ -0,0 +1,241 @@
+ENV:
+  BACKEND: nccl
+#
+SOLVER:
+  NAME: LatentDiffusionSolver
+  RESUME_FROM:
+  LOAD_MODEL_ONLY: True
+  USE_FSDP: False
+  SHARDING_STRATEGY:
+  USE_AMP: True
+  DTYPE: float16
+  CHANNELS_LAST: True
+  MAX_STEPS: 500
+  MAX_EPOCHS: -1
+  NUM_FOLDS: 1
+  ACCU_STEP: 1
+  EVAL_INTERVAL: 50
+  RESCALE_LR: False
+  #
+  WORK_DIR: ./cache/save_data/dit_sd3_1024_lora
+  LOG_FILE: std_log.txt
+  #
+  FILE_SYSTEM:
+    - NAME: "ModelscopeFs"
+      TEMP_DIR: ./cache/cache_data
+  #
+  TUNER:
+    - NAME: SwiftLoRA
+      R: 128
+      LORA_ALPHA: 128
+      LORA_DROPOUT: 0.0
+      BIAS: "none"
+      TARGET_MODULES: "model.*(.attn.qkv|.attn.proj|mlp.fc1|mlp.fc2)$"
+  #
+  MODEL:
+    NAME: LatentDiffusionSD3
+    PARAMETERIZATION: rf
+    TIMESTEPS: 1000
+    MIN_SNR_GAMMA:
+    ZERO_TERMINAL_SNR: False
+    PRETRAINED_MODEL:
+    IGNORE_KEYS: [ ]
+    SCALE_FACTOR: 1.5305
+    SHIFT_FACTOR: 0.0609
+    DEFAULT_N_PROMPT:
+    SCHEDULE_ARGS:
+      "NAME": "shifted"
+      "SHIFT": 3
+    USE_EMA: False
+    T_WEIGHT: uniform
+    #
+    DIFFUSION_MODEL:
+      NAME: MMDiT
+      PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium@sd3_medium.safetensors
+      IGNORE_KEYS: '^first_stage_model.'
+      IN_CHANNELS: 16
+      PATCH_SIZE: 2
+      OUT_CHANNELS: 16
+      DEPTH: 24
+      INPUT_SIZE:
+      ADM_IN_CHANNELS: 2048
+      CONTEXT_EMBEDDER_CONFIG: { 'target': 'torch.nn.Linear', 'params': { 'in_features': 4096, 'out_features': 1536 } }
+      NUM_PATCHES: 36864
+      POS_EMBED_MAX_SIZE: 192
+      POS_EMBED_SCALING_FACTOR:
+      USE_CHECKPOINT: True
+    #
+    FIRST_STAGE_MODEL:
+      NAME: AutoencoderKL
+      PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium@sd3_medium.safetensors
+      EMBED_DIM: 16
+      IGNORE_KEYS: '^model.diffusion_model.'
+      BATCH_SIZE: 1
+      USE_CONV: False
+      #
+      ENCODER:
+        NAME: Encoder
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 16
+        DOUBLE_Z: True
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+      #
+      DECODER:
+        NAME: Decoder
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 16
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+        GIVE_PRE_END: False
+        TANH_OUT: False
+    #
+    COND_STAGE_MODEL:
+      NAME: SD3TextEmbedder
+      P_ZERO: 0.0
+      CLIP_L:
+        NAME: FrozenCLIPEmbedder2
+        PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@text_encoder
+        TOKENIZER_PATH: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@tokenizer
+        MAX_LENGTH: 77
+        FREEZE: True
+        LAYER: penultimate
+        RETURN_POOLED: True
+        USE_FINAL_LAYER_NORM: False
+        IS_TRAINABLE: False
+      CLIP_G:
+        NAME: FrozenCLIPEmbedder2
+        PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@text_encoder_2
+        TOKENIZER_PATH: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@tokenizer_2
+        MAX_LENGTH: 77
+        FREEZE: True
+        LAYER: penultimate
+        RETURN_POOLED: True
+        USE_FINAL_LAYER_NORM: False
+        IS_TRAINABLE: False
+      T5_XXL:
+        NAME: T5EmbedderHF
+        PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@text_encoder_3
+        TOKENIZER_PATH: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@tokenizer_3
+        LENGTH: 256
+        CLEAN: whitespace
+        USE_GRAD: False
+        T5_DTYPE: float16
+    #
+    LOSS:
+      NAME: ReconstructLoss
+      LOSS_TYPE: l2
+  #
+  SAMPLE_ARGS:
+    SAMPLER: euler
+    SAMPLE_STEPS: 28
+    SEED: 1749023094
+    GUIDE_SCALE: 5.0
+    GUIDE_RESCALE: 0.0
+    DISCRETIZATION: trailing
+    RUN_TRAIN_N: False
+  #
+  OPTIMIZER:
+    NAME: AdamW
+    LEARNING_RATE: 5e-5
+    BETAS: [ 0.9, 0.999 ]
+    EPS: 1e-8
+    WEIGHT_DECAY: 1e-2
+    AMSGRAD: False
+  #
+  TRAIN_DATA:
+    NAME: ImageTextPairMSDataset
+    MODE: train
+    MS_DATASET_NAME: style_custom_dataset
+    MS_DATASET_NAMESPACE: damo
+    MS_DATASET_SUBNAME: 3D
+    PROMPT_PREFIX: ""
+    MS_DATASET_SPLIT: train
+    MS_REMAP_KEYS: { 'Image:FILE': 'Target:FILE' }
+    REPLACE_STYLE: False
+    PIN_MEMORY: True
+    BATCH_SIZE: 1
+    NUM_WORKERS: 4
+    SAMPLER:
+      NAME: LoopSampler
+    TRANSFORMS:
+      - NAME: LoadImageFromFile
+        RGB_ORDER: RGB
+        BACKEND: pillow
+      - NAME: FlexibleResize
+        INTERPOLATION: bilinear
+        SIZE: [ 1024, 1024 ]
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'img' ]
+        BACKEND: pillow
+      - NAME: FlexibleCenterCrop
+        SIZE: [ 1024, 1024 ]
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'img' ]
+        BACKEND: pillow
+      - NAME: ImageToTensor
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'img' ]
+        BACKEND: pillow
+      - NAME: Normalize
+        MEAN: [ 0.5,  0.5,  0.5 ]
+        STD: [ 0.5,  0.5,  0.5 ]
+        INPUT_KEY: [ 'img' ]
+        OUTPUT_KEY: [ 'image' ]
+        BACKEND: torchvision
+      - NAME: Select
+        KEYS: [ 'image', 'prompt' ]
+        META_KEYS: [ 'data_key' ]
+  #
+  EVAL_DATA:
+    NAME: Text2ImageDataset
+    MODE: eval
+    PROMPT_FILE:
+    PROMPT_DATA: [ "a cat holds a blackboard that writes \"hello world\"", "a dog running on the lawn" ]
+    IMAGE_SIZE: [ 1024, 1024 ]
+    FIELDS: [ "prompt" ]
+    DELIMITER: '#;#'
+    PROMPT_PREFIX: ''
+    PIN_MEMORY: True
+    BATCH_SIZE: 1
+    NUM_WORKERS: 4
+    TRANSFORMS:
+      - NAME: Select
+        KEYS: [ 'index', 'prompt' ]
+        META_KEYS: [ 'image_size' ]
+  #
+  TRAIN_HOOKS:
+    -
+      NAME: BackwardHook
+      PRIORITY: 10000
+    -
+      NAME: LogHook
+      LOG_INTERVAL: 10
+      SHOW_GPU_MEM: True
+    -
+      NAME: TensorboardLogHook
+    -
+      NAME: CheckpointHook
+      INTERVAL: 10000
+      PRIORITY: 200
+      SAVE_LAST: True
+      SAVE_NAME_PREFIX: 'step'
+      DISABLE_SNAPSHOT: True
+  #
+  EVAL_HOOKS:
+    -
+      NAME: ProbeDataHook
+      PROB_INTERVAL: 50
+      SAVE_LAST: True
+      SAVE_NAME_PREFIX: 'step'
+      SAVE_PROBE_PREFIX: 'image'
@@ -14,13 +14,14 @@ SOLVER:
  NUM_FOLDS: 1
  ACCU_STEP: 1
  EVAL_INTERVAL: 100
+  RESCALE_LR: False
  #
  WORK_DIR: ./cache/save_data/sd15_512_full
  LOG_FILE: std_log.txt
  #
  FILE_SYSTEM:
    NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
  #
  MODEL:
    NAME: LatentDiffusion
@@ -124,7 +125,7 @@ SOLVER:
  #
  OPTIMIZER:
    NAME: AdamW
-    LEARNING_RATE: 0.0064
+    LEARNING_RATE: 0.00001
    BETAS: [ 0.9, 0.999 ]
    EPS: 1e-8
    WEIGHT_DECAY: 1e-2
@@ -190,7 +191,7 @@ SOLVER:
    NUM_WORKERS: 4
    FILE_SYSTEM:
      NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
    #
    TRANSFORMS:
      -
@@ -14,13 +14,14 @@ SOLVER:
  NUM_FOLDS: 1
  ACCU_STEP: 1
  EVAL_INTERVAL: 100
+  RESCALE_LR: False
  #
  WORK_DIR: ./cache/save_data/sd15_512_lora
  LOG_FILE: std_log.txt
  #
  FILE_SYSTEM:
    NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
  TUNER:
    -
      NAME: SwiftLoRA
@@ -132,7 +133,7 @@ SOLVER:
  #
  OPTIMIZER:
    NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
    BETAS: [ 0.9, 0.999 ]
    EPS: 1e-8
    WEIGHT_DECAY: 1e-2
@@ -198,7 +199,7 @@ SOLVER:
    NUM_WORKERS: 4
    FILE_SYSTEM:
      NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
    #
    TRANSFORMS:
      -
@@ -14,13 +14,14 @@ SOLVER:
  NUM_FOLDS: 1
  ACCU_STEP: 1
  EVAL_INTERVAL: 100
+  RESCALE_LR: False
  #
  WORK_DIR: ./cache/save_data/sd15_512_textlora
  LOG_FILE: std_log.txt
  #
  FILE_SYSTEM:
    NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
  TUNER:
    -
      NAME: SwiftLoRA
@@ -140,7 +141,7 @@ SOLVER:
  #
  OPTIMIZER:
    NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
    BETAS: [ 0.9, 0.999 ]
    EPS: 1e-8
    WEIGHT_DECAY: 1e-2
@@ -206,7 +207,7 @@ SOLVER:
    NUM_WORKERS: 4
    FILE_SYSTEM:
      NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
    #
    TRANSFORMS:
      -
@@ -14,13 +14,14 @@ SOLVER:
  NUM_FOLDS: 1
  ACCU_STEP: 1
  EVAL_INTERVAL: 100
+  RESCALE_LR: False
  #
  WORK_DIR: ./cache/save_data/sd21_512_full
  LOG_FILE: std_log.txt
  #
  FILE_SYSTEM:
    NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
  #
  MODEL:
    NAME: LatentDiffusion
@@ -120,7 +121,7 @@ SOLVER:
  #
  OPTIMIZER:
    NAME: AdamW
-    LEARNING_RATE: 0.0064
+    LEARNING_RATE: 0.00001
    BETAS: [ 0.9, 0.999 ]
    EPS: 1e-8
    WEIGHT_DECAY: 1e-2
@@ -186,7 +187,7 @@ SOLVER:
    NUM_WORKERS: 4
    FILE_SYSTEM:
      NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
    #
    TRANSFORMS:
      -
@@ -14,13 +14,14 @@ SOLVER:
  NUM_FOLDS: 1
  ACCU_STEP: 1
  EVAL_INTERVAL: 100
+  RESCALE_LR: False
  #
  WORK_DIR: ./cache/save_data/sd21_512_lora
  LOG_FILE: std_log.txt
  #
  FILE_SYSTEM:
    NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
  #
  TUNER:
    -
@@ -129,7 +130,7 @@ SOLVER:
  #
  OPTIMIZER:
    NAME: AdamW
-    LEARNING_RATE: 0.0064
+    LEARNING_RATE: 0.00001
    BETAS: [ 0.9, 0.999 ]
    EPS: 1e-8
    WEIGHT_DECAY: 1e-2
@@ -195,7 +196,7 @@ SOLVER:
    NUM_WORKERS: 4
    FILE_SYSTEM:
      NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
    #
    TRANSFORMS:
      -
@@ -14,13 +14,14 @@ SOLVER:
  NUM_FOLDS: 1
  ACCU_STEP: 1
  EVAL_INTERVAL: 100
+  RESCALE_LR: False
  #
  WORK_DIR: ./cache/save_data/sd21_768_full
  LOG_FILE: std_log.txt
  #
  FILE_SYSTEM:
    NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
  #
  MODEL:
    NAME: LatentDiffusion
@@ -120,7 +121,7 @@ SOLVER:
  #
  OPTIMIZER:
    NAME: AdamW
-    LEARNING_RATE: 0.0064
+    LEARNING_RATE: 0.00001
    BETAS: [ 0.9, 0.999 ]
    EPS: 1e-8
    WEIGHT_DECAY: 1e-2
@@ -186,7 +187,7 @@ SOLVER:
    NUM_WORKERS: 4
    FILE_SYSTEM:
      NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
    #
    TRANSFORMS:
      -
@@ -14,13 +14,14 @@ SOLVER:
  NUM_FOLDS: 1
  ACCU_STEP: 1
  EVAL_INTERVAL: 100
+  RESCALE_LR: False
  #
  WORK_DIR: ./cache/save_data/sd21_768_lora
  LOG_FILE: std_log.txt
  #
  FILE_SYSTEM:
    NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
  #
  TUNER:
    -
@@ -129,7 +130,7 @@ SOLVER:
  #
  OPTIMIZER:
    NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
    BETAS: [ 0.9, 0.999 ]
    EPS: 1e-8
    WEIGHT_DECAY: 1e-2
@@ -195,7 +196,7 @@ SOLVER:
    NUM_WORKERS: 4
    FILE_SYSTEM:
      NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
    #
    TRANSFORMS:
      -
@@ -14,13 +14,14 @@ SOLVER:
  NUM_FOLDS: 1
  ACCU_STEP: 1
  EVAL_INTERVAL: 100
+  RESCALE_LR: False
  #
  WORK_DIR: ./cache/save_data/sdxl_1024_full
  LOG_FILE: std_log.txt
  #
  FILE_SYSTEM:
    NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
  #
  MODEL:
    NAME: LatentDiffusionXL
@@ -238,7 +239,7 @@ SOLVER:
  #
  OPTIMIZER:
    NAME: AdamW
-    LEARNING_RATE: 0.0064
+    LEARNING_RATE: 0.00001
    BETAS: [ 0.9, 0.999 ]
    EPS: 1e-8
    WEIGHT_DECAY: 1e-2
@@ -306,7 +307,7 @@ SOLVER:
    NUM_WORKERS: 4
    FILE_SYSTEM:
      NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
    #
    TRANSFORMS:
      - NAME: Select
@@ -14,13 +14,14 @@ SOLVER:
  NUM_FOLDS: 1
  ACCU_STEP: 1
  EVAL_INTERVAL: 100
+  RESCALE_LR: False
  #
  WORK_DIR: ./cache/save_data/sdxl_1024_lora
  LOG_FILE: std_log.txt
  #
  FILE_SYSTEM:
    NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
  #
  TUNER:
    -
@@ -247,7 +248,7 @@ SOLVER:
  #
  OPTIMIZER:
    NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
    BETAS: [ 0.9, 0.999 ]
    EPS: 1e-8
    WEIGHT_DECAY: 1e-2
@@ -315,7 +316,7 @@ SOLVER:
    NUM_WORKERS: 4
    FILE_SYSTEM:
      NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
    #
    TRANSFORMS:
      - NAME: Select
@@ -14,13 +14,14 @@ SOLVER:
  NUM_FOLDS: 1
  ACCU_STEP: 1
  EVAL_INTERVAL: 100
+  RESCALE_LR: False
  #
  WORK_DIR: ./cache/save_data/sdxl_1024_textlora
  LOG_FILE: std_log.txt
  #
  FILE_SYSTEM:
    NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
  #
  TUNER:
    -
@@ -255,7 +256,7 @@ SOLVER:
  #
  OPTIMIZER:
    NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
    BETAS: [ 0.9, 0.999 ]
    EPS: 1e-8
    WEIGHT_DECAY: 1e-2
@@ -323,7 +324,7 @@ SOLVER:
    NUM_WORKERS: 4
    FILE_SYSTEM:
      NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
    #
    TRANSFORMS:
      - NAME: Select
@@ -14,13 +14,14 @@ SOLVER:
  NUM_FOLDS: 1
  ACCU_STEP: 1
  EVAL_INTERVAL: 100
+  RESCALE_LR: False
  #
  WORK_DIR: ./cache/save_data/sd15_512_sce_ctr_hed
  LOG_FILE: std_log.txt
  #
  FILE_SYSTEM:
    NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
  #
  FREEZE:
    FREEZE_PART: [ "first_stage_model", "cond_stage_model", "model" ]
@@ -127,7 +128,7 @@ SOLVER:
        DOWN_RATIO: 1.0
    CONTROL_ANNO:
      NAME: HedAnnotator
-      PRETRAINED_MODEL: ms://damo/scepter_scedit@annotator/ckpts/ControlNetHED.pth
+      PRETRAINED_MODEL: ms://iic/scepter_scedit@annotator/ckpts/ControlNetHED.pth
  #
  SAMPLE_ARGS:
    SAMPLER: ddim
@@ -141,7 +142,7 @@ SOLVER:
  #
  OPTIMIZER:
    NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
    BETAS: [ 0.9, 0.999 ]
    EPS: 1e-8
    WEIGHT_DECAY: 1e-2
@@ -167,13 +168,13 @@ SOLVER:
        RGB_ORDER: RGB
        BACKEND: pillow
      - NAME: Resize
-        SIZE: 768
+        SIZE: 512
        INTERPOLATION: bilinear
        INPUT_KEY: [ 'img' ]
        OUTPUT_KEY: [ 'img' ]
        BACKEND: pillow
      - NAME: CenterCrop
-        SIZE: 768
+        SIZE: 512
        INPUT_KEY: [ 'img' ]
        OUTPUT_KEY: [ 'img' ]
        BACKEND: pillow
@@ -215,13 +216,13 @@ SOLVER:
        RGB_ORDER: RGB
        BACKEND: pillow
      - NAME: Resize
-        SIZE: 768
+        SIZE: 512
        INTERPOLATION: bilinear
        INPUT_KEY: [ 'img' ]
        OUTPUT_KEY: [ 'img' ]
        BACKEND: pillow
      - NAME: CenterCrop
-        SIZE: 768
+        SIZE: 512
        INPUT_KEY: [ 'img' ]
        OUTPUT_KEY: [ 'img' ]
        BACKEND: pillow
@@ -14,13 +14,14 @@ SOLVER:
  NUM_FOLDS: 1
  ACCU_STEP: 1
  EVAL_INTERVAL: 100
+  RESCALE_LR: False
  #
  WORK_DIR: ./cache/save_data/sd21_768_sce_ctr_canny
  LOG_FILE: std_log.txt
  #
  FILE_SYSTEM:
    NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
  #
  FREEZE:
    FREEZE_PART: [ "first_stage_model", "cond_stage_model", "model" ]
@@ -140,7 +141,7 @@ SOLVER:
  #
  OPTIMIZER:
    NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
    BETAS: [ 0.9, 0.999 ]
    EPS: 1e-8
    WEIGHT_DECAY: 1e-2
@@ -14,13 +14,14 @@ SOLVER:
  NUM_FOLDS: 1
  ACCU_STEP: 1
  EVAL_INTERVAL: 100
+  RESCALE_LR: False
  #
  WORK_DIR: ./cache/save_data/sd21_768_sce_ctr_pose
  LOG_FILE: std_log.txt
  #
  FILE_SYSTEM:
    NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
  #
  FREEZE:
    FREEZE_PART: [ "first_stage_model", "cond_stage_model", "model" ]
@@ -125,8 +126,8 @@ SOLVER:
        DOWN_RATIO: 1.0
    CONTROL_ANNO:
      NAME: OpenposeAnnotator
-      BODY_MODEL_PATH: ms://damo/scepter_scedit@annotator/ckpts/body_pose_model.pth
-      HAND_MODEL_PATH: ms://damo/scepter_scedit@annotator/ckpts/hand_pose_model.pth
+      BODY_MODEL_PATH: ms://iic/scepter_scedit@annotator/ckpts/body_pose_model.pth
+      HAND_MODEL_PATH: ms://iic/scepter_scedit@annotator/ckpts/hand_pose_model.pth
  #
  SAMPLE_ARGS:
    SAMPLER: ddim
@@ -140,7 +141,7 @@ SOLVER:
  #
  OPTIMIZER:
    NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
    BETAS: [ 0.9, 0.999 ]
    EPS: 1e-8
    WEIGHT_DECAY: 1e-2
@@ -14,13 +14,14 @@ SOLVER:
  NUM_FOLDS: 1
  ACCU_STEP: 1
  EVAL_INTERVAL: 100
+  RESCALE_LR: False
  #
  WORK_DIR: ./cache/save_data/sdxl_1024_sce_ctr_canny
  LOG_FILE: std_log.txt
  #
  FILE_SYSTEM:
    NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
  #
  FREEZE:
    FREEZE_PART: [ "first_stage_model", "cond_stage_model", "model" ]
@@ -254,7 +255,7 @@ SOLVER:
  #
  OPTIMIZER:
    NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
    BETAS: [ 0.9, 0.999 ]
    EPS: 1e-8
    WEIGHT_DECAY: 1e-2
@@ -14,13 +14,14 @@ SOLVER:
  NUM_FOLDS: 1
  ACCU_STEP: 1
  EVAL_INTERVAL: 100
+  RESCALE_LR: False
  #
  WORK_DIR: ./cache/save_data/sdxl_1024_sce_ctr_color
  LOG_FILE: std_log.txt
  #
  FILE_SYSTEM:
    NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
  #
  FREEZE:
    FREEZE_PART: [ "first_stage_model", "cond_stage_model", "model" ]
@@ -255,7 +256,7 @@ SOLVER:
  #
  OPTIMIZER:
    NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
    BETAS: [ 0.9, 0.999 ]
    EPS: 1e-8
    WEIGHT_DECAY: 1e-2
@@ -14,13 +14,14 @@ SOLVER:
  NUM_FOLDS: 1
  ACCU_STEP: 1
  EVAL_INTERVAL: 100
+  RESCALE_LR: False
  #
  WORK_DIR: ./cache/save_data/sdxl_1024_sce_ctr_color_datatxt
  LOG_FILE: std_log.txt
  #
  FILE_SYSTEM:
    NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
  #
  FREEZE:
    FREEZE_PART: [ "first_stage_model", "cond_stage_model", "model" ]
@@ -255,7 +256,7 @@ SOLVER:
  #
  OPTIMIZER:
    NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
    BETAS: [ 0.9, 0.999 ]
    EPS: 1e-8
    WEIGHT_DECAY: 1e-2
@@ -14,13 +14,14 @@ SOLVER:
  NUM_FOLDS: 1
  ACCU_STEP: 1
  EVAL_INTERVAL: 100
+  RESCALE_LR: False
  #
  WORK_DIR: ./cache/save_data/sdxl_1024_sce_ctr_depth
  LOG_FILE: std_log.txt
  #
  FILE_SYSTEM:
    NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
  #
  FREEZE:
    FREEZE_PART: [ "first_stage_model", "cond_stage_model", "model" ]
@@ -241,7 +242,7 @@ SOLVER:
        DOWN_RATIO: 1.0
    CONTROL_ANNO:
      NAME: MidasDetector
-      PRETRAINED_MODEL: ms://damo/scepter_scedit@annotator/ckpts/dpt_hybrid-midas-501f0c75.pt
+      PRETRAINED_MODEL: ms://iic/scepter_scedit@annotator/ckpts/dpt_hybrid-midas-501f0c75.pt
  #
  SAMPLE_ARGS:
    SAMPLER: ddim
@@ -255,7 +256,7 @@ SOLVER:
  #
  OPTIMIZER:
    NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
    BETAS: [ 0.9, 0.999 ]
    EPS: 1e-8
    WEIGHT_DECAY: 1e-2
@@ -14,13 +14,14 @@ SOLVER:
  NUM_FOLDS: 1
  ACCU_STEP: 1
  EVAL_INTERVAL: 100
+  RESCALE_LR: False
  #
  WORK_DIR: ./cache/save_data/sd15_512_sce_t2i
  LOG_FILE: std_log.txt
  #
  FILE_SYSTEM:
    NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
  #
  FREEZE:
    FREEZE_PART: [ "first_stage_model", "cond_stage_model", "model" ]
@@ -134,7 +135,7 @@ SOLVER:
  #
  OPTIMIZER:
    NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
    BETAS: [ 0.9, 0.999 ]
    EPS: 1e-8
    WEIGHT_DECAY: 1e-2
@@ -200,7 +201,7 @@ SOLVER:
    NUM_WORKERS: 4
    FILE_SYSTEM:
      NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
    #
    TRANSFORMS:
      -
@@ -14,13 +14,14 @@ SOLVER:
  NUM_FOLDS: 1
  ACCU_STEP: 1
  EVAL_INTERVAL: 100
+  RESCALE_LR: False
  #
  WORK_DIR: ./cache/save_data/sd15_512_sce_t2i_swift
  LOG_FILE: std_log.txt
  #
  FILE_SYSTEM:
    NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
  #
  TUNER:
    -
@@ -132,7 +133,7 @@ SOLVER:
  #
  OPTIMIZER:
    NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
    BETAS: [ 0.9, 0.999 ]
    EPS: 1e-8
    WEIGHT_DECAY: 1e-2
@@ -198,7 +199,7 @@ SOLVER:
    NUM_WORKERS: 4
    FILE_SYSTEM:
      NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
    #
    TRANSFORMS:
      -
@@ -14,13 +14,14 @@ SOLVER:
  NUM_FOLDS: 1
  ACCU_STEP: 1
  EVAL_INTERVAL: 100
+  RESCALE_LR: False
  #
  WORK_DIR: ./cache/save_data/sd15_512_textsce_t2i_swift
  LOG_FILE: std_log.txt
  #
  FILE_SYSTEM:
    NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
  #
  TUNER:
    -
@@ -140,7 +141,7 @@ SOLVER:
  #
  OPTIMIZER:
    NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
    BETAS: [ 0.9, 0.999 ]
    EPS: 1e-8
    WEIGHT_DECAY: 1e-2
@@ -206,7 +207,7 @@ SOLVER:
    NUM_WORKERS: 4
    FILE_SYSTEM:
      NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
    #
    TRANSFORMS:
      -
@@ -14,13 +14,14 @@ SOLVER:
  NUM_FOLDS: 1
  ACCU_STEP: 1
  EVAL_INTERVAL: 100
+  RESCALE_LR: False
  #
  WORK_DIR: ./cache/save_data/sd21_768_sce_t2i
  LOG_FILE: std_log.txt
  #
  FILE_SYSTEM:
    NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
  #
  FREEZE:
    FREEZE_PART: [ "first_stage_model", "cond_stage_model", "model" ]
@@ -130,7 +131,7 @@ SOLVER:
  #
  OPTIMIZER:
    NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
    BETAS: [ 0.9, 0.999 ]
    EPS: 1e-8
    WEIGHT_DECAY: 1e-2
@@ -196,7 +197,7 @@ SOLVER:
    NUM_WORKERS: 4
    FILE_SYSTEM:
      NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
    #
    TRANSFORMS:
      -
@@ -14,13 +14,14 @@ SOLVER:
  NUM_FOLDS: 1
  ACCU_STEP: 1
  EVAL_INTERVAL: 100
+  RESCALE_LR: False
  #
  WORK_DIR: ./cache/save_data/sd21_768_sce_t2i_swift
  LOG_FILE: std_log.txt
  #
  FILE_SYSTEM:
    NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
  #
  TUNER:
    -
@@ -128,7 +129,7 @@ SOLVER:
  #
  OPTIMIZER:
    NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
    BETAS: [ 0.9, 0.999 ]
    EPS: 1e-8
    WEIGHT_DECAY: 1e-2
@@ -194,7 +195,7 @@ SOLVER:
    NUM_WORKERS: 4
    FILE_SYSTEM:
      NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
    #
    TRANSFORMS:
      -
@@ -14,13 +14,14 @@ SOLVER:
  NUM_FOLDS: 1
  ACCU_STEP: 1
  EVAL_INTERVAL: 100
+  RESCALE_LR: False
  #
  WORK_DIR: ./cache/save_data/sdxl_1024_sce_t2i
  LOG_FILE: std_log.txt
  #
  FILE_SYSTEM:
    NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
  #
  FREEZE:
    FREEZE_PART: [ "first_stage_model", "cond_stage_model", "model" ]
@@ -247,7 +248,7 @@ SOLVER:
  #
  OPTIMIZER:
    NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
    BETAS: [ 0.9, 0.999 ]
    EPS: 1e-8
    WEIGHT_DECAY: 1e-2
@@ -315,7 +316,7 @@ SOLVER:
    NUM_WORKERS: 4
    FILE_SYSTEM:
      NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
    #
    TRANSFORMS:
      - NAME: Select
@@ -14,13 +14,14 @@ SOLVER:
  NUM_FOLDS: 1
  ACCU_STEP: 1
  EVAL_INTERVAL: 100
+  RESCALE_LR: False
  #
  WORK_DIR: ./cache/save_data/sdxl_1024_sce_t2i_datatxt
  LOG_FILE: std_log.txt
  #
  FILE_SYSTEM:
    NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
  #
  FREEZE:
    FREEZE_PART: [ "first_stage_model", "cond_stage_model", "model" ]
@@ -247,7 +248,7 @@ SOLVER:
  #
  OPTIMIZER:
    NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
    BETAS: [ 0.9, 0.999 ]
    EPS: 1e-8
    WEIGHT_DECAY: 1e-2
@@ -14,13 +14,14 @@ SOLVER:
  NUM_FOLDS: 1
  ACCU_STEP: 1
  EVAL_INTERVAL: 100
+  RESCALE_LR: False
  #
  WORK_DIR: ./cache/save_data/sdxl_1024_sce_t2i_swift
  LOG_FILE: std_log.txt
  #
  FILE_SYSTEM:
    NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
  #
  TUNER:
    -
@@ -245,7 +246,7 @@ SOLVER:
  #
  OPTIMIZER:
    NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
    BETAS: [ 0.9, 0.999 ]
    EPS: 1e-8
    WEIGHT_DECAY: 1e-2
@@ -313,7 +314,7 @@ SOLVER:
    NUM_WORKERS: 4
    FILE_SYSTEM:
      NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
    #
    TRANSFORMS:
      - NAME: Select
@@ -14,13 +14,14 @@ SOLVER:
  NUM_FOLDS: 1
  ACCU_STEP: 1
  EVAL_INTERVAL: 100
+  RESCALE_LR: False
  #
  WORK_DIR: ./cache/save_data/sdxl_1024_textsce_t2i_swift
  LOG_FILE: std_log.txt
  #
  FILE_SYSTEM:
    NAME: "ModelscopeFs"
-    TEMP_DIR: "./cache/data"
+    TEMP_DIR: "./cache/cache_data"
  #
  TUNER:
    -
@@ -253,7 +254,7 @@ SOLVER:
  #
  OPTIMIZER:
    NAME: AdamW
-    LEARNING_RATE: 0.064
+    LEARNING_RATE: 0.0001
    BETAS: [ 0.9, 0.999 ]
    EPS: 1e-8
    WEIGHT_DECAY: 1e-2
@@ -321,7 +322,7 @@ SOLVER:
    NUM_WORKERS: 4
    FILE_SYSTEM:
      NAME: "ModelscopeFs"
-      TEMP_DIR: "./cache/data"
+      TEMP_DIR: "./cache/cache_data"
    #
    TRANSFORMS:
      - NAME: Select
@@ -0,0 +1,25 @@
+WORK_DIR: chatbot
+FILE_SYSTEM:
+  - NAME: LocalFs
+    TEMP_DIR: ./cache/cache_data
+  - NAME: ModelscopeFs
+    TEMP_DIR: ./cache/cache_data
+  - NAME: HuggingfaceFs
+    TEMP_DIR: ./cache/cache_data
+#
+ENABLE_I2V: False
+SKIP_EXAMPLES: True
+#
+MODEL:
+  EDIT_MODEL:
+    MODEL_CFG_DIR: scepter/methods/studio/chatbot/models/
+  I2V:
+    MODEL_NAME: CogVideoX-5b-I2V
+    MODEL_DIR: ms://ZhipuAI/CogVideoX-5b-I2V/
+  CAPTIONER:
+    MODEL_NAME: InternVL2-2B
+    MODEL_DIR: ms://OpenGVLab/InternVL2-2B/
+    PROMPT: '<image>\nThis image is the first frame of a video. Based on this image, please imagine what changes may occur in the next few seconds of the video. Please output brief description, such as "a dog running" or "a person turns to left". No more than 30 words.'
+  ENHANCER:
+    MODEL_NAME: Meta-Llama-3.1-8B-Instruct
+    MODEL_DIR: ms://LLM-Research/Meta-Llama-3.1-8B-Instruct/
@@ -0,0 +1,128 @@
+NAME: ACE_0.6B_1024
+IS_DEFAULT: False
+USE_DYNAMIC_MODEL: True
+DEFAULT_PARAS:
+  PARAS:
+  #
+  INPUT:
+    INPUT_IMAGE:
+    INPUT_MASK:
+    TASK:
+    PROMPT: ""
+    NEGATIVE_PROMPT: ""
+    OUTPUT_HEIGHT: 1024
+    OUTPUT_WIDTH: 1024
+    SAMPLER: ddim
+    SAMPLE_STEPS: 50
+    GUIDE_SCALE: 4.5
+    GUIDE_RESCALE: 0.5
+    SEED: -1
+    TAR_INDEX: 0
+  OUTPUT:
+    LATENT:
+    IMAGES:
+    SEED:
+  MODULES_PARAS:
+    FIRST_STAGE_MODEL:
+      FUNCTION:
+        - NAME: encode
+          DTYPE: float16
+          INPUT: ["IMAGE"]
+        - NAME: decode
+          DTYPE: float16
+          INPUT: ["LATENT"]
+    #
+    DIFFUSION_MODEL:
+      FUNCTION:
+        - NAME: forward
+          DTYPE: float16
+          INPUT: ["SAMPLE_STEPS", "SAMPLE", "GUIDE_SCALE"]
+    #
+    COND_STAGE_MODEL:
+      FUNCTION:
+        - NAME: encode_list_of_list
+          DTYPE: bfloat16
+          INPUT: ["PROMPT"]
+#
+MODEL:
+  NAME: LatentDiffusionACE
+  PRETRAINED_MODEL:
+  IGNORE_KEYS: [ ]
+  SCALE_FACTOR: 0.18215
+  SIZE_FACTOR: 8
+  DECODER_BIAS: 0.5
+  DEFAULT_N_PROMPT: ""
+  TEXT_IDENTIFIER: [ '{image}', '{image1}', '{image2}', '{image3}', '{image4}', '{image5}', '{image6}', '{image7}', '{image8}', '{image9}' ]
+  USE_TEXT_POS_EMBEDDINGS: True
+  #
+  DIFFUSION:
+    NAME: BaseDiffusion
+    PREDICTION_TYPE: eps
+    MIN_SNR_GAMMA:
+    NOISE_SCHEDULER:
+      NAME: LinearScheduler
+      NUM_TIMESTEPS: 1000
+      BETA_MIN: 0.0001
+      BETA_MAX: 0.02
+  #
+  DIFFUSION_MODEL:
+    NAME: ACE
+    PRETRAINED_MODEL: ms://iic/ACE-0.6B-1024px@models/dit/ace_0.6b_1024px.pth
+    IGNORE_KEYS: [ ]
+    PATCH_SIZE: 2
+    IN_CHANNELS: 4
+    HIDDEN_SIZE: 1152
+    DEPTH: 28
+    NUM_HEADS: 16
+    MLP_RATIO: 4.0
+    PRED_SIGMA: True
+    DROP_PATH: 0.0
+    WINDOW_DIZE: 0
+    Y_CHANNELS: 4096
+    MAX_SEQ_LEN: 4096
+    QK_NORM: True
+    USE_GRAD_CHECKPOINT: True
+    ATTENTION_BACKEND: flash_attn
+  #
+  FIRST_STAGE_MODEL:
+    NAME: AutoencoderKL
+    EMBED_DIM: 4
+    PRETRAINED_MODEL: ms://iic/ACE-0.6B-1024px@models/vae/vae.bin
+    IGNORE_KEYS: []
+    #
+    ENCODER:
+      NAME: Encoder
+      CH: 128
+      OUT_CH: 3
+      NUM_RES_BLOCKS: 2
+      IN_CHANNELS: 3
+      ATTN_RESOLUTIONS: [ ]
+      CH_MULT: [ 1, 2, 4, 4 ]
+      Z_CHANNELS: 4
+      DOUBLE_Z: True
+      DROPOUT: 0.0
+      RESAMP_WITH_CONV: True
+    #
+    DECODER:
+      NAME: Decoder
+      CH: 128
+      OUT_CH: 3
+      NUM_RES_BLOCKS: 2
+      IN_CHANNELS: 3
+      ATTN_RESOLUTIONS: [ ]
+      CH_MULT: [ 1, 2, 4, 4 ]
+      Z_CHANNELS: 4
+      DROPOUT: 0.0
+      RESAMP_WITH_CONV: True
+      GIVE_PRE_END: False
+      TANH_OUT: False
+  #
+  COND_STAGE_MODEL:
+    NAME: T5EmbedderHF
+    PRETRAINED_MODEL: ms://iic/ACE-0.6B-1024px@models/text_encoder/t5-v1_1-xxl/
+    TOKENIZER_PATH: ms://iic/ACE-0.6B-1024px@models/tokenizer/t5-v1_1-xxl
+    LENGTH: 120
+    T5_DTYPE: bfloat16
+    ADDED_IDENTIFIER: [ '{image}', '{caption}', '{mask}', '{ref_image}', '{image1}', '{image2}', '{image3}', '{image4}', '{image5}', '{image6}', '{image7}', '{image8}', '{image9}' ]
+    CLEAN: whitespace
+    USE_GRAD: False
@@ -0,0 +1,284 @@
+NAME: ACE_0.6B_1024_REFINER
+IS_DEFAULT: False
+USE_DYNAMIC_MODEL: True
+DEFAULT_PARAS:
+  PARAS:
+  #
+  INPUT:
+    INPUT_IMAGE:
+    INPUT_MASK:
+    TASK:
+    PROMPT: ""
+    NEGATIVE_PROMPT: ""
+    OUTPUT_HEIGHT: 1024
+    OUTPUT_WIDTH: 1024
+    SAMPLER: ddim
+    SAMPLE_STEPS: 50
+    GUIDE_SCALE: 4.5
+    GUIDE_RESCALE: 0.5
+    SEED: -1
+    TAR_INDEX: 0
+    REFINER_SCALE: 0.2
+    USE_ACE: True
+    #REFINER_PROMPT: "High Resolution, Sharpness, Clarity, Detail Enhancement, Noise Reduction, HD, 4k, Image Restoration, HDR"
+    REFINER_PROMPT: "High Resolution, Sharpness, Clarity, Detail Enhancement, Noise Reduction, HD, 4k, Image Restoration, HDR"
+  OUTPUT:
+    LATENT:
+    IMAGES:
+    SEED:
+  MODULES_PARAS:
+    FIRST_STAGE_MODEL:
+      FUNCTION:
+        - NAME: encode
+          DTYPE: float16
+          INPUT: ["IMAGE"]
+        - NAME: decode
+          DTYPE: float16
+          INPUT: ["LATENT"]
+    #
+    DIFFUSION_MODEL:
+      FUNCTION:
+        - NAME: forward
+          DTYPE: float16
+          INPUT: ["SAMPLE_STEPS", "SAMPLE", "GUIDE_SCALE"]
+    #
+    COND_STAGE_MODEL:
+      FUNCTION:
+        - NAME: encode_list_of_list
+          DTYPE: bfloat16
+          INPUT: ["PROMPT"]
+#
+MODEL:
+  NAME: LatentDiffusionACE
+  PRETRAINED_MODEL:
+  IGNORE_KEYS: [ ]
+  SCALE_FACTOR: 0.18215
+  SIZE_FACTOR: 8
+  DECODER_BIAS: 0.5
+  DEFAULT_N_PROMPT: ""
+  TEXT_IDENTIFIER: [ '{image}', '{image1}', '{image2}', '{image3}', '{image4}', '{image5}', '{image6}', '{image7}', '{image8}', '{image9}' ]
+  USE_TEXT_POS_EMBEDDINGS: True
+  #
+  DIFFUSION:
+    NAME: BaseDiffusion
+    PREDICTION_TYPE: eps
+    MIN_SNR_GAMMA:
+    NOISE_SCHEDULER:
+      NAME: LinearScheduler
+      NUM_TIMESTEPS: 1000
+      BETA_MIN: 0.0001
+      BETA_MAX: 0.02
+  #
+  DIFFUSION_MODEL:
+    NAME: ACE
+    PRETRAINED_MODEL: ms://iic/ACE-0.6B-1024px@models/dit/ace_0.6b_1024px.pth
+    IGNORE_KEYS: [ ]
+    PATCH_SIZE: 2
+    IN_CHANNELS: 4
+    HIDDEN_SIZE: 1152
+    DEPTH: 28
+    NUM_HEADS: 16
+    MLP_RATIO: 4.0
+    PRED_SIGMA: True
+    DROP_PATH: 0.0
+    WINDOW_DIZE: 0
+    Y_CHANNELS: 4096
+    MAX_SEQ_LEN: 4096
+    QK_NORM: True
+    USE_GRAD_CHECKPOINT: True
+    ATTENTION_BACKEND: flash_attn
+  #
+  FIRST_STAGE_MODEL:
+    NAME: AutoencoderKL
+    EMBED_DIM: 4
+    PRETRAINED_MODEL: ms://iic/ACE-0.6B-1024px@models/vae/vae.bin
+    IGNORE_KEYS: []
+    #
+    ENCODER:
+      NAME: Encoder
+      CH: 128
+      OUT_CH: 3
+      NUM_RES_BLOCKS: 2
+      IN_CHANNELS: 3
+      ATTN_RESOLUTIONS: [ ]
+      CH_MULT: [ 1, 2, 4, 4 ]
+      Z_CHANNELS: 4
+      DOUBLE_Z: True
+      DROPOUT: 0.0
+      RESAMP_WITH_CONV: True
+    #
+    DECODER:
+      NAME: Decoder
+      CH: 128
+      OUT_CH: 3
+      NUM_RES_BLOCKS: 2
+      IN_CHANNELS: 3
+      ATTN_RESOLUTIONS: [ ]
+      CH_MULT: [ 1, 2, 4, 4 ]
+      Z_CHANNELS: 4
+      DROPOUT: 0.0
+      RESAMP_WITH_CONV: True
+      GIVE_PRE_END: False
+      TANH_OUT: False
+  #
+  COND_STAGE_MODEL:
+    NAME: T5EmbedderHF
+    PRETRAINED_MODEL: ms://iic/ACE-0.6B-1024px@models/text_encoder/t5-v1_1-xxl/
+    TOKENIZER_PATH: ms://iic/ACE-0.6B-1024px@models/tokenizer/t5-v1_1-xxl
+    LENGTH: 120
+    T5_DTYPE: bfloat16
+    ADDED_IDENTIFIER: [ '{image}', '{caption}', '{mask}', '{ref_image}', '{image1}', '{image2}', '{image3}', '{image4}', '{image5}', '{image6}', '{image7}', '{image8}', '{image9}' ]
+    CLEAN: whitespace
+    USE_GRAD: False
+
+ACE_PROMPT: [
+  "A cute cartoon rabbit holding a whiteboard that says 'ACE Refiner', standing in a sunny meadow filled with flowers, with a big smile and bright colors.",
+  "A beautiful young woman with long flowing hair, wearing a summer dress, holding a whiteboard that reads 'ACE Refiner' while sitting on a park bench surrounded by cherry blossoms.",
+  "An adorable cartoon cat wearing oversized glasses, holding a whiteboard that says 'ACE Refiner', perched on a stack of colorful books in a cozy library setting.",
+  "A charming girl with pigtails, wearing a cute school uniform, enthusiastically holding a whiteboard that has 'ACE Refiner' written on it, in a bright and cheerful classroom full of educational posters.",
+  "A friendly cartoon dog with floppy ears, sitting in front of a doghouse, proudly holding a whiteboard that says 'ACE Refiner', with a playful expression and a blue sky in the background.",
+  "A cute anime girl with big expressive eyes, dressed in a colorful outfit, holding a whiteboard that reads 'ACE Refiner' in a fantastical landscape filled with mythical creatures.",
+  "A vibrant cartoon fox holding a whiteboard that says 'ACE Refiner', standing on a rock by a sparkling stream, surrounded by lush greenery and butterflies.",
+  "A stylish young woman in a business outfit, smiling as she holds a whiteboard written with 'ACE Refiner', in a modern office filled with plants and natural light.",
+  "A cute cartoon unicorn holding a sparkling whiteboard that says 'ACE Refiner', frolicking in a magical forest, with rainbows and stars in the background.",
+  "A happy family, consisting of a cute little girl and her playful puppy, holding a whiteboard that says 'ACE Refiner', together in their backyard on a sunny day."
+]
+REFINER_MODEL:
+  NAME: ""
+  IS_DEFAULT: False
+  DEFAULT_PARAS:
+    PARAS:
+      RESOLUTIONS: [ [ 1024, 1024 ] ]
+    INPUT:
+      INPUT_IMAGE:
+      INPUT_MASK:
+      TASK:
+      PROMPT: ""
+      NEGATIVE_PROMPT: ""
+      OUTPUT_HEIGHT: 1024
+      OUTPUT_WIDTH: 1024
+      SAMPLER: flow_euler
+      SAMPLE_STEPS: 30
+      GUIDE_SCALE: 3.5
+      GUIDE_RESCALE:
+    OUTPUT:
+      LATENT:
+      IMAGES:
+      SEED:
+    MODULES_PARAS:
+      FIRST_STAGE_MODEL:
+        FUNCTION:
+          - NAME: encode
+            DTYPE: bfloat16
+            INPUT: [ "IMAGE" ]
+          - NAME: decode
+            DTYPE: bfloat16
+            INPUT: [ "LATENT" ]
+        PARAS:
+          SCALE_FACTOR: 1.5305
+          SHIFT_FACTOR: 0.0609
+          SIZE_FACTOR: 8
+      DIFFUSION_MODEL:
+        FUNCTION:
+          - NAME: forward
+            DTYPE: bfloat16
+            INPUT: [ "SAMPLE_STEPS", "SAMPLE", "GUIDE_SCALE" ]
+      COND_STAGE_MODEL:
+        FUNCTION:
+          - NAME: encode
+            DTYPE: bfloat16
+            INPUT: [ "PROMPT" ]
+
+  MODEL:
+    DIFFUSION:
+      NAME: DiffusionFluxRF
+      PREDICTION_TYPE: raw
+      NOISE_SCHEDULER:
+        NAME: FlowMatchSigmaScheduler
+        WEIGHTING_SCHEME: logit_normal
+        SHIFT: 3.0
+        LOGIT_MEAN: 0.0
+        LOGIT_STD: 1.0
+        MODE_SCALE: 1.29
+    DIFFUSION_MODEL:
+      NAME: FluxMR
+      PRETRAINED_MODEL: ms://AI-ModelScope/FLUX.1-dev@flux1-dev.safetensors
+      IN_CHANNELS: 64
+      OUT_CHANNELS: 64
+      HIDDEN_SIZE: 3072
+      NUM_HEADS: 24
+      AXES_DIM: [ 16, 56, 56 ]
+      THETA: 10000
+      VEC_IN_DIM: 768
+      GUIDANCE_EMBED: True
+      CONTEXT_IN_DIM: 4096
+      MLP_RATIO: 4.0
+      QKV_BIAS: True
+      DEPTH: 19
+      DEPTH_SINGLE_BLOCKS: 38
+      USE_GRAD_CHECKPOINT: True
+      ATTN_BACKEND: flash_attn
+    #
+    FIRST_STAGE_MODEL:
+      NAME: AutoencoderKLFlux
+      EMBED_DIM: 16
+      PRETRAINED_MODEL:  ms://AI-ModelScope/FLUX.1-dev@ae.safetensors
+      IGNORE_KEYS: [ ]
+      BATCH_SIZE: 8
+      USE_CONV: False
+      SCALE_FACTOR: 0.3611
+      SHIFT_FACTOR: 0.1159
+      #
+      ENCODER:
+        NAME: Encoder
+        USE_CHECKPOINT: False
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 16
+        DOUBLE_Z: True
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+      #
+      DECODER:
+        NAME: Decoder
+        USE_CHECKPOINT: False
+        CH: 128
+        OUT_CH: 3
+        NUM_RES_BLOCKS: 2
+        IN_CHANNELS: 3
+        ATTN_RESOLUTIONS: [ ]
+        CH_MULT: [ 1, 2, 4, 4 ]
+        Z_CHANNELS: 16
+        DROPOUT: 0.0
+        RESAMP_WITH_CONV: True
+        GIVE_PRE_END: False
+        TANH_OUT: False
+    #
+    COND_STAGE_MODEL:
+      NAME: T5PlusClipFluxEmbedder
+      T5_MODEL:
+        NAME: HFEmbedder
+        HF_MODEL_CLS: T5EncoderModel
+        MODEL_PATH: ms://AI-ModelScope/FLUX.1-dev@text_encoder_2/
+        HF_TOKENIZER_CLS: T5Tokenizer
+        TOKENIZER_PATH: ms://AI-ModelScope/FLUX.1-dev@tokenizer_2/
+        MAX_LENGTH: 512
+        OUTPUT_KEY: last_hidden_state
+        D_TYPE: bfloat16
+        BATCH_INFER: False
+        CLEAN: whitespace
+      CLIP_MODEL:
+        NAME: HFEmbedder
+        HF_MODEL_CLS: CLIPTextModel
+        MODEL_PATH: ms://AI-ModelScope/FLUX.1-dev@text_encoder/
+        HF_TOKENIZER_CLS: CLIPTokenizer
+        TOKENIZER_PATH: ms://AI-ModelScope/FLUX.1-dev@tokenizer/
+        MAX_LENGTH: 77
+        OUTPUT_KEY: pooler_output
+        D_TYPE: bfloat16
+        BATCH_INFER: True
+        CLEAN: whitespace
@@ -0,0 +1,128 @@
+NAME: ACE_0.6B_512
+IS_DEFAULT: True
+USE_DYNAMIC_MODEL: True
+DEFAULT_PARAS:
+  PARAS:
+  #
+  INPUT:
+    INPUT_IMAGE:
+    INPUT_MASK:
+    TASK:
+    PROMPT: ""
+    NEGATIVE_PROMPT: ""
+    OUTPUT_HEIGHT: 512
+    OUTPUT_WIDTH: 512
+    SAMPLER: ddim
+    SAMPLE_STEPS: 20
+    GUIDE_SCALE: 4.5
+    GUIDE_RESCALE: 0.5
+    SEED: -1
+    TAR_INDEX: 0
+  OUTPUT:
+    LATENT:
+    IMAGES:
+    SEED:
+  MODULES_PARAS:
+    FIRST_STAGE_MODEL:
+      FUNCTION:
+        - NAME: encode
+          DTYPE: float16
+          INPUT: ["IMAGE"]
+        - NAME: decode
+          DTYPE: float16
+          INPUT: ["LATENT"]
+    #
+    DIFFUSION_MODEL:
+      FUNCTION:
+        - NAME: forward
+          DTYPE: float16
+          INPUT: ["SAMPLE_STEPS", "SAMPLE", "GUIDE_SCALE"]
+    #
+    COND_STAGE_MODEL:
+      FUNCTION:
+        - NAME: encode_list_of_list
+          DTYPE: bfloat16
+          INPUT: ["PROMPT"]
+#
+MODEL:
+  NAME: LatentDiffusionACE
+  PRETRAINED_MODEL:
+  IGNORE_KEYS: [ ]
+  SCALE_FACTOR: 0.18215
+  SIZE_FACTOR: 8
+  DECODER_BIAS: 0.5
+  DEFAULT_N_PROMPT: ""
+  TEXT_IDENTIFIER: [ '{image}', '{image1}', '{image2}', '{image3}', '{image4}', '{image5}', '{image6}', '{image7}', '{image8}', '{image9}' ]
+  USE_TEXT_POS_EMBEDDINGS: True
+  #
+  DIFFUSION:
+    NAME: BaseDiffusion
+    PREDICTION_TYPE: eps
+    MIN_SNR_GAMMA:
+    NOISE_SCHEDULER:
+      NAME: LinearScheduler
+      NUM_TIMESTEPS: 1000
+      BETA_MIN: 0.0001
+      BETA_MAX: 0.02
+  #
+  DIFFUSION_MODEL:
+    NAME: ACE
+    PRETRAINED_MODEL: ms://iic/ACE-0.6B-512px@models/dit/ace_0.6b_512px.pth
+    IGNORE_KEYS: [ ]
+    PATCH_SIZE: 2
+    IN_CHANNELS: 4
+    HIDDEN_SIZE: 1152
+    DEPTH: 28
+    NUM_HEADS: 16
+    MLP_RATIO: 4.0
+    PRED_SIGMA: True
+    DROP_PATH: 0.0
+    WINDOW_DIZE: 0
+    Y_CHANNELS: 4096
+    MAX_SEQ_LEN: 1024
+    QK_NORM: True
+    USE_GRAD_CHECKPOINT: True
+    ATTENTION_BACKEND: flash_attn
+  #
+  FIRST_STAGE_MODEL:
+    NAME: AutoencoderKL
+    EMBED_DIM: 4
+    PRETRAINED_MODEL: ms://iic/ACE-0.6B-512px@models/vae/vae.bin
+    IGNORE_KEYS: []
+    #
+    ENCODER:
+      NAME: Encoder
+      CH: 128
+      OUT_CH: 3
+      NUM_RES_BLOCKS: 2
+      IN_CHANNELS: 3
+      ATTN_RESOLUTIONS: [ ]
+      CH_MULT: [ 1, 2, 4, 4 ]
+      Z_CHANNELS: 4
+      DOUBLE_Z: True
+      DROPOUT: 0.0
+      RESAMP_WITH_CONV: True
+    #
+    DECODER:
+      NAME: Decoder
+      CH: 128
+      OUT_CH: 3
+      NUM_RES_BLOCKS: 2
+      IN_CHANNELS: 3
+      ATTN_RESOLUTIONS: [ ]
+      CH_MULT: [ 1, 2, 4, 4 ]
+      Z_CHANNELS: 4
+      DROPOUT: 0.0
+      RESAMP_WITH_CONV: True
+      GIVE_PRE_END: False
+      TANH_OUT: False
+  #
+  COND_STAGE_MODEL:
+    NAME: T5EmbedderHF
+    PRETRAINED_MODEL: ms://iic/ACE-0.6B-512px@models/text_encoder/t5-v1_1-xxl/
+    TOKENIZER_PATH: ms://iic/ACE-0.6B-512px@models/tokenizer/t5-v1_1-xxl
+    LENGTH: 120
+    T5_DTYPE: bfloat16
+    ADDED_IDENTIFIER: [ '{image}', '{caption}', '{mask}', '{ref_image}', '{image1}', '{image2}', '{image3}', '{image4}', '{image5}', '{image6}', '{image7}', '{image8}', '{image9}' ]
+    CLEAN: whitespace
+    USE_GRAD: False
@@ -5,59 +5,59 @@ CONTROLLERS:
    DESCRIPTION:
    BASE_MODEL: SD2.1
    TYPE: Canny
-    MODEL_PATH: ms://damo/scepter_scedit@controllable_model/SD2.1/canny_control/
+    MODEL_PATH: ms://iic/scepter_scedit@controllable_model/SD2.1/canny_control/
  - NAME: openpose
    NAME_ZH:
    DESCRIPTION:
    BASE_MODEL: SD2.1
    TYPE: Openpose
-    MODEL_PATH: ms://damo/scepter_scedit@controllable_model/SD2.1/pose_control/
+    MODEL_PATH: ms://iic/scepter_scedit@controllable_model/SD2.1/pose_control/
  - NAME: color
    NAME_ZH:
    DESCRIPTION:
    BASE_MODEL: SD2.1
    TYPE: Color
-    MODEL_PATH: ms://damo/scepter_scedit@controllable_model/SD2.1/color_control/
+    MODEL_PATH: ms://iic/scepter_scedit@controllable_model/SD2.1/color_control/
  - NAME: hed
    NAME_ZH:
    DESCRIPTION:
    BASE_MODEL: SD2.1
    TYPE: Hed
-    MODEL_PATH: ms://damo/scepter_scedit@controllable_model/SD2.1/hed_control
+    MODEL_PATH: ms://iic/scepter_scedit@controllable_model/SD2.1/hed_control
  - NAME: depth
    NAME_ZH:
    DESCRIPTION:
    BASE_MODEL: SD2.1
    TYPE: Midas
-    MODEL_PATH: ms://damo/scepter_scedit@controllable_model/SD2.1/depth_control
+    MODEL_PATH: ms://iic/scepter_scedit@controllable_model/SD2.1/depth_control
  # SD_XL1.0
  - NAME: canny
    NAME_ZH:
    DESCRIPTION:
    BASE_MODEL: SD_XL1.0
    TYPE: Canny
-    MODEL_PATH: ms://damo/scepter_scedit@controllable_model/SD_XL1.0/canny_control
+    MODEL_PATH: ms://iic/scepter_scedit@controllable_model/SD_XL1.0/canny_control
  - NAME: color
    NAME_ZH:
    DESCRIPTION:
    BASE_MODEL: SD_XL1.0
    TYPE: Color
-    MODEL_PATH: ms://damo/scepter_scedit@controllable_model/SD_XL1.0/color_control
+    MODEL_PATH: ms://iic/scepter_scedit@controllable_model/SD_XL1.0/color_control
  - NAME: depth
    NAME_ZH:
    DESCRIPTION:
    BASE_MODEL: SD_XL1.0
    TYPE: Midas
-    MODEL_PATH: ms://damo/scepter_scedit@controllable_model/SD_XL1.0/depth_control
+    MODEL_PATH: ms://iic/scepter_scedit@controllable_model/SD_XL1.0/depth_control
  - NAME: hed
    NAME_ZH:
    DESCRIPTION:
    BASE_MODEL: SD_XL1.0
    TYPE: Hed
-    MODEL_PATH: ms://damo/scepter_scedit@controllable_model/SD_XL1.0/hed_control
+    MODEL_PATH: ms://iic/scepter_scedit@controllable_model/SD_XL1.0/hed_control
  - NAME: openpose
    NAME_ZH:
    DESCRIPTION:
    BASE_MODEL: SD_XL1.0
    TYPE: Openpose
-    MODEL_PATH: ms://damo/scepter_scedit@controllable_model/SD_XL1.0/pose_control
+    MODEL_PATH: ms://iic/scepter_scedit@controllable_model/SD_XL1.0/pose_control
@@ -1,11 +1,20 @@
 TUNERS:
+  - NAME: Clay-Style-Editing
+    NAME_ZH: 黏土风
+    SOURCE: scepter
+    DESCRIPTION: None
+    BASE_MODEL: EDIT
+    MODEL_PATH: ms://iic/stylebooth@tuners/clay_style_edit/
+    IMAGE_PATH: ms://iic/stylebooth@tuners/clay_style_edit/image.jpg
+    TUNER_TYPE: LORA
+    PROMPT_EXAMPLE: Convert this image into clay style
  - NAME: Azure-Dragon
    NAME_ZH: 青龙
    SOURCE: scepter
    DESCRIPTION: None
    BASE_MODEL: SD_XL1.0
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/azure_dragon/
-    IMAGE_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/azure_dragon/xl_azure_dragon.png
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/azure_dragon/
+    IMAGE_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/azure_dragon/xl_azure_dragon.png
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: Azure Dragon, 8K, high quality,Ultra High Detail.One of the Four Divine Creatures in Charge of Water.
  - NAME: Gold-Dragon
@@ -13,8 +22,8 @@ TUNERS:
    SOURCE: scepter
    DESCRIPTION: None
    BASE_MODEL: SD_XL1.0
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/gold_dragon/
-    IMAGE_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/gold_dragon/xl_gold_dragon.png
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/gold_dragon/
+    IMAGE_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/gold_dragon/xl_gold_dragon.png
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: Chinese Gold Dragon in the clouds. Translucent Texture. Zbrush.  Fuzzy Art. Exquisite Craftsmanship. 3D. 8K. Ultra High Detail
  - NAME: SpringFestival-Dragon
@@ -22,8 +31,8 @@ TUNERS:
    SOURCE: scepter
    DESCRIPTION: None
    BASE_MODEL: SD_XL1.0
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/spring_festival_dragon/
-    IMAGE_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/spring_festival_dragon/xl_spring_festival_dragon.png
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/spring_festival_dragon/
+    IMAGE_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/spring_festival_dragon/xl_spring_festival_dragon.png
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: Chinese dragon. Spring Festival.Festive.Street.Lanterns.32K.High quality.expressive, dramatic, dreamlike and mysterious, Surrealism
  - NAME: Red-Dragon
@@ -31,8 +40,8 @@ TUNERS:
    SOURCE: scepter
    DESCRIPTION: None
    BASE_MODEL: SD_XL1.0
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/red_dragon/
-    IMAGE_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/red_dragon/xl_red_dragon.png
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/red_dragon/
+    IMAGE_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/red_dragon/xl_red_dragon.png
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: Traditional Red Dragon of China. Low Water Level. Studio Ghibli Style. Mural Illustration. White Background. High Detail
  - NAME: ChinesePunk-Dragon
@@ -40,8 +49,8 @@ TUNERS:
    SOURCE: scepter
    DESCRIPTION: None
    BASE_MODEL: SD_XL1.0
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/chinese_punk_dragon/
-    IMAGE_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/chinese_punk_dragon/xl_chinese_punk_dragon.png
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/chinese_punk_dragon/
+    IMAGE_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/chinese_punk_dragon/xl_chinese_punk_dragon.png
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: uhd Image,Dragon,Chinese Dragon, Dunhuang Mural Style, Traditional Maritime Art Style
  - NAME: Cute-Dragon
@@ -49,8 +58,8 @@ TUNERS:
    SOURCE: scepter
    DESCRIPTION: None
    BASE_MODEL: SD_XL1.0
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/cute_dragon/
-    IMAGE_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/cute_dragon/xl_kawaii_dragon.png
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/cute_dragon/
+    IMAGE_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/cute_dragon/xl_kawaii_dragon.png
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: China Kawaii Dragon. Contest Winner. Minimalist Illustration. White Background. Flat Style. Digital Painting Style. Red. 32k uhd. Fun Comics. Fuzzy Art. Bold. Comic-Inspired Characters
  - NAME: Dragon-Baby
@@ -58,8 +67,8 @@ TUNERS:
    SOURCE: scepter
    DESCRIPTION: None
    BASE_MODEL: SD_XL1.0
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/baby_dragon/
-    IMAGE_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/baby_dragon/xl_baby_dragon.png
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/baby_dragon/
+    IMAGE_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/baby_dragon/xl_baby_dragon.png
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: Warm Colors, Soft,Chinese Dragon Baby, Felt Style,Dragon Baby, Best Quality, 3D Doll, Macaron Tones, Glittering Big Eyes, Winter,Dragon
  - NAME: Sloppy-Dragon
@@ -67,8 +76,8 @@ TUNERS:
    SOURCE: scepter
    DESCRIPTION: None
    BASE_MODEL: SD_XL1.0
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/sloppy_dragon/
-    IMAGE_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/sloppy_dragon/xl_sloppy_dragon.png
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/sloppy_dragon/
+    IMAGE_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/sloppy_dragon/xl_sloppy_dragon.png
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: Messy Chinese Dragon,Cute, Wu Guanzhong, Rough
  -
@@ -77,8 +86,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: diva
    BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/894f40ed44b37c3372e6a22b8ae577a4.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/Caricature
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/894f40ed44b37c3372e6a22b8ae577a4.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/Caricature
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -87,8 +96,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: diva
    BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/894f40ed44b37c3372e6a22b8ae577a4.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/Caricature
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/894f40ed44b37c3372e6a22b8ae577a4.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/Caricature
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -97,8 +106,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: diva
    BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/894f40ed44b37c3372e6a22b8ae577a4.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/Caricature
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/894f40ed44b37c3372e6a22b8ae577a4.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/Caricature
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -107,8 +116,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: diva
    BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/80e5b4075c572c04cbb4e48c37b8366b.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/ColorFieldPainting
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/80e5b4075c572c04cbb4e48c37b8366b.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/ColorFieldPainting
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -117,8 +126,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: diva
    BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/80e5b4075c572c04cbb4e48c37b8366b.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/ColorFieldPainting
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/80e5b4075c572c04cbb4e48c37b8366b.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/ColorFieldPainting
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -127,8 +136,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: diva
    BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/80e5b4075c572c04cbb4e48c37b8366b.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/ColorFieldPainting
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/80e5b4075c572c04cbb4e48c37b8366b.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/ColorFieldPainting
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -137,8 +146,8 @@ TUNERS:
    DESCRIPTION:
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    BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/9ae235d7f1a7c2a4edab52a5e9f9cbae.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/ColoredPencilArt
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/9ae235d7f1a7c2a4edab52a5e9f9cbae.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/ColoredPencilArt
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -147,8 +156,8 @@ TUNERS:
    DESCRIPTION:
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-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/9ae235d7f1a7c2a4edab52a5e9f9cbae.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/ColoredPencilArt
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/9ae235d7f1a7c2a4edab52a5e9f9cbae.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/ColoredPencilArt
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -157,8 +166,8 @@ TUNERS:
    DESCRIPTION:
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-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/9ae235d7f1a7c2a4edab52a5e9f9cbae.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/ColoredPencilArt
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/9ae235d7f1a7c2a4edab52a5e9f9cbae.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/ColoredPencilArt
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -167,8 +176,8 @@ TUNERS:
    DESCRIPTION:
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-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/3da915da2f5cedaf243e57e08163f35b.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/DarkMoodyAtmosphere
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/3da915da2f5cedaf243e57e08163f35b.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/DarkMoodyAtmosphere
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -177,8 +186,8 @@ TUNERS:
    DESCRIPTION:
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    BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/3da915da2f5cedaf243e57e08163f35b.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/DarkMoodyAtmosphere
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/3da915da2f5cedaf243e57e08163f35b.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/DarkMoodyAtmosphere
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -187,8 +196,8 @@ TUNERS:
    DESCRIPTION:
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    BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/3da915da2f5cedaf243e57e08163f35b.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/DarkMoodyAtmosphere
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/3da915da2f5cedaf243e57e08163f35b.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/DarkMoodyAtmosphere
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -197,8 +206,8 @@ TUNERS:
    DESCRIPTION:
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    BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/69fd81f5983107acc3d334af62915851.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/DrippingPaintSplatterArt
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/69fd81f5983107acc3d334af62915851.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/DrippingPaintSplatterArt
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -207,8 +216,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: diva
    BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/69fd81f5983107acc3d334af62915851.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/DrippingPaintSplatterArt
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/69fd81f5983107acc3d334af62915851.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/DrippingPaintSplatterArt
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -217,8 +226,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: diva
    BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/69fd81f5983107acc3d334af62915851.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/DrippingPaintSplatterArt
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/69fd81f5983107acc3d334af62915851.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/DrippingPaintSplatterArt
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -227,8 +236,8 @@ TUNERS:
    DESCRIPTION:
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    BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/f152edb4b3ca6248758b48115258ddfa.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/FadedPolaroidPhoto
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/f152edb4b3ca6248758b48115258ddfa.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/FadedPolaroidPhoto
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -237,8 +246,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: diva
    BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/f152edb4b3ca6248758b48115258ddfa.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/FadedPolaroidPhoto
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/f152edb4b3ca6248758b48115258ddfa.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/FadedPolaroidPhoto
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -247,8 +256,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: diva
    BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/f152edb4b3ca6248758b48115258ddfa.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/FadedPolaroidPhoto
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/f152edb4b3ca6248758b48115258ddfa.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/FadedPolaroidPhoto
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -257,8 +266,8 @@ TUNERS:
    DESCRIPTION:
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    BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/940cfd34155634cf051e1b2942cca426.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/Flat2DArt
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/940cfd34155634cf051e1b2942cca426.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/Flat2DArt
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -267,8 +276,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: diva
    BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/940cfd34155634cf051e1b2942cca426.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/Flat2DArt
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/940cfd34155634cf051e1b2942cca426.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/Flat2DArt
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -277,8 +286,8 @@ TUNERS:
    DESCRIPTION:
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    BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/940cfd34155634cf051e1b2942cca426.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/Flat2DArt
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/940cfd34155634cf051e1b2942cca426.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/Flat2DArt
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -287,8 +296,8 @@ TUNERS:
    DESCRIPTION:
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-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/57b751b11564cb22cd49ef21f2004a5f.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/GraffitiArt
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/57b751b11564cb22cd49ef21f2004a5f.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/GraffitiArt
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -297,8 +306,8 @@ TUNERS:
    DESCRIPTION:
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    BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/57b751b11564cb22cd49ef21f2004a5f.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/GraffitiArt
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/57b751b11564cb22cd49ef21f2004a5f.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/GraffitiArt
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -307,8 +316,8 @@ TUNERS:
    DESCRIPTION:
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    BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/57b751b11564cb22cd49ef21f2004a5f.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/GraffitiArt
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/57b751b11564cb22cd49ef21f2004a5f.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/GraffitiArt
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -317,8 +326,8 @@ TUNERS:
    DESCRIPTION:
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-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/0312b673dc6858a9864d7f45f0c5c1fc.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/Impressionism
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/0312b673dc6858a9864d7f45f0c5c1fc.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/Impressionism
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -327,8 +336,8 @@ TUNERS:
    DESCRIPTION:
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-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/0312b673dc6858a9864d7f45f0c5c1fc.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/Impressionism
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/0312b673dc6858a9864d7f45f0c5c1fc.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/Impressionism
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -337,8 +346,8 @@ TUNERS:
    DESCRIPTION:
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-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/0312b673dc6858a9864d7f45f0c5c1fc.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/Impressionism
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/0312b673dc6858a9864d7f45f0c5c1fc.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/Impressionism
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -347,8 +356,8 @@ TUNERS:
    DESCRIPTION:
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-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/9aa040b0c60d289da9610c91ad9b7c7e.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/LogoDesign
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/9aa040b0c60d289da9610c91ad9b7c7e.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/LogoDesign
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
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    DESCRIPTION:
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-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/9aa040b0c60d289da9610c91ad9b7c7e.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/LogoDesign
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/9aa040b0c60d289da9610c91ad9b7c7e.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/LogoDesign
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
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    DESCRIPTION:
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-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/9aa040b0c60d289da9610c91ad9b7c7e.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/LogoDesign
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/9aa040b0c60d289da9610c91ad9b7c7e.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/LogoDesign
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
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-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/PencilSketchDrawing
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/a9056e1eac85e5e4fe96a93917d4cce4.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/PencilSketchDrawing
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
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    DESCRIPTION:
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-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/PencilSketchDrawing
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/a9056e1eac85e5e4fe96a93917d4cce4.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/PencilSketchDrawing
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
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-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/a9056e1eac85e5e4fe96a93917d4cce4.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/PencilSketchDrawing
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/a9056e1eac85e5e4fe96a93917d4cce4.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/PencilSketchDrawing
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
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-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/SilhouetteArt
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/568777f447fc02510b618152726d5002.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/SilhouetteArt
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
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-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/SilhouetteArt
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/568777f447fc02510b618152726d5002.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/SilhouetteArt
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
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    DESCRIPTION:
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-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/SilhouetteArt
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/568777f447fc02510b618152726d5002.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/SilhouetteArt
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
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-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/Steampunk2
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/07d7b27cd73f2d43684003563511c15b.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/Steampunk2
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
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-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/Steampunk2
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/07d7b27cd73f2d43684003563511c15b.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/Steampunk2
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
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-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/Steampunk2
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/07d7b27cd73f2d43684003563511c15b.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/Steampunk2
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -467,8 +476,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: diva
    BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/2d1e9867058db2c57f2fe47530de3243.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/StickerDesigns
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/2d1e9867058db2c57f2fe47530de3243.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/StickerDesigns
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -477,8 +486,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: diva
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-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/2d1e9867058db2c57f2fe47530de3243.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/StickerDesigns
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/2d1e9867058db2c57f2fe47530de3243.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/StickerDesigns
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -487,8 +496,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: diva
    BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/2d1e9867058db2c57f2fe47530de3243.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/StickerDesigns
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/2d1e9867058db2c57f2fe47530de3243.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/StickerDesigns
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -497,8 +506,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: diva
    BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/8859d532ae5901cc8457d6118fb9b7da.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/Watercolor2
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/8859d532ae5901cc8457d6118fb9b7da.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/Watercolor2
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -507,8 +516,8 @@ TUNERS:
    DESCRIPTION:
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    BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/8859d532ae5901cc8457d6118fb9b7da.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/Watercolor2
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/8859d532ae5901cc8457d6118fb9b7da.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/Watercolor2
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -517,8 +526,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: diva
    BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/8859d532ae5901cc8457d6118fb9b7da.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/Watercolor2
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/8859d532ae5901cc8457d6118fb9b7da.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/Watercolor2
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -527,8 +536,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: mre
    BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/5895d78cf58c1ca05178991f37cc48ff.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/mre-elemental-art
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/5895d78cf58c1ca05178991f37cc48ff.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/mre-elemental-art
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -537,8 +546,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: mre
    BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/5895d78cf58c1ca05178991f37cc48ff.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/mre-elemental-art
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/5895d78cf58c1ca05178991f37cc48ff.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/mre-elemental-art
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -547,8 +556,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: mre
    BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/5895d78cf58c1ca05178991f37cc48ff.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/mre-elemental-art
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/5895d78cf58c1ca05178991f37cc48ff.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/mre-elemental-art
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -557,8 +566,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: mre
    BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/a08149bc8e50f6bc65c0010d4cd416f8.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/mre-anime
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/a08149bc8e50f6bc65c0010d4cd416f8.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/mre-anime
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -567,8 +576,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: mre
    BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/a08149bc8e50f6bc65c0010d4cd416f8.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/mre-anime
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/a08149bc8e50f6bc65c0010d4cd416f8.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/mre-anime
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -577,8 +586,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: mre
    BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/a08149bc8e50f6bc65c0010d4cd416f8.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/mre-anime
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/a08149bc8e50f6bc65c0010d4cd416f8.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/mre-anime
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -587,8 +596,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: mre
    BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/48c65cebf1fa4284d7b8feb619412e65.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/mre-comic
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/48c65cebf1fa4284d7b8feb619412e65.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/mre-comic
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -597,8 +606,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: mre
    BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/48c65cebf1fa4284d7b8feb619412e65.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/mre-comic
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/48c65cebf1fa4284d7b8feb619412e65.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/mre-comic
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -607,8 +616,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: mre
    BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/48c65cebf1fa4284d7b8feb619412e65.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/mre-comic
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/48c65cebf1fa4284d7b8feb619412e65.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/mre-comic
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -617,8 +626,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: sai
    BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/8fc51113f725f27326c4398a7457cd6d.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/sai-craftclay
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/8fc51113f725f27326c4398a7457cd6d.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/sai-craftclay
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -627,8 +636,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: sai
    BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/8fc51113f725f27326c4398a7457cd6d.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/sai-craftclay
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/8fc51113f725f27326c4398a7457cd6d.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/sai-craftclay
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -637,8 +646,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: sai
    BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/8fc51113f725f27326c4398a7457cd6d.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/sai-craftclay
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/8fc51113f725f27326c4398a7457cd6d.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/sai-craftclay
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -647,8 +656,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: sai
    BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/a6f8d92afcd5803dfb2ebecbc92091b6.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/sai-fantasyart
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/a6f8d92afcd5803dfb2ebecbc92091b6.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/sai-fantasyart
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -657,8 +666,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: sai
    BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/a6f8d92afcd5803dfb2ebecbc92091b6.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/sai-fantasyart
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/a6f8d92afcd5803dfb2ebecbc92091b6.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/sai-fantasyart
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -667,8 +676,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: sai
    BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/a6f8d92afcd5803dfb2ebecbc92091b6.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/sai-fantasyart
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/a6f8d92afcd5803dfb2ebecbc92091b6.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/sai-fantasyart
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -677,8 +686,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: sai
    BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/034a51b0dd34b018be8859bf45b4f7ed.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/sai-lineart
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/034a51b0dd34b018be8859bf45b4f7ed.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/sai-lineart
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -687,8 +696,8 @@ TUNERS:
    DESCRIPTION:
    SOURCE: sai
    BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/034a51b0dd34b018be8859bf45b4f7ed.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/sai-lineart
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/034a51b0dd34b018be8859bf45b4f7ed.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/sai-lineart
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -697,8 +706,8 @@ TUNERS:
    DESCRIPTION:
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    BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/034a51b0dd34b018be8859bf45b4f7ed.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/sai-lineart
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/034a51b0dd34b018be8859bf45b4f7ed.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/sai-lineart
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -707,8 +716,8 @@ TUNERS:
    DESCRIPTION:
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    BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/7e9ed25bb34008beb5f417df63c4b2fe.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/sai-neonpunk
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/7e9ed25bb34008beb5f417df63c4b2fe.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/sai-neonpunk
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -717,8 +726,8 @@ TUNERS:
    DESCRIPTION:
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    BASE_MODEL: SD2.1
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/7e9ed25bb34008beb5f417df63c4b2fe.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/sai-neonpunk
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/7e9ed25bb34008beb5f417df63c4b2fe.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/sai-neonpunk
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -727,8 +736,8 @@ TUNERS:
    DESCRIPTION:
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    BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/7e9ed25bb34008beb5f417df63c4b2fe.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/sai-neonpunk
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/7e9ed25bb34008beb5f417df63c4b2fe.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/sai-neonpunk
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -737,8 +746,8 @@ TUNERS:
    DESCRIPTION:
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    BASE_MODEL: SD_XL1.0
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD_XL1.0/924f46a8f276011a0953d7988e90ee25.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/sai-origami
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/924f46a8f276011a0953d7988e90ee25.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/sai-origami
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -747,8 +756,8 @@ TUNERS:
    DESCRIPTION:
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-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/924f46a8f276011a0953d7988e90ee25.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/sai-origami
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/924f46a8f276011a0953d7988e90ee25.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/sai-origami
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -757,8 +766,8 @@ TUNERS:
    DESCRIPTION:
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-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/924f46a8f276011a0953d7988e90ee25.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/sai-origami
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/924f46a8f276011a0953d7988e90ee25.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/sai-origami
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -767,8 +776,8 @@ TUNERS:
    DESCRIPTION:
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    BASE_MODEL: SD_XL1.0
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-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD_XL1.0/sai-pixelart
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD_XL1.0/a5ab89c0960be8c1216e65c98d92ae4a.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD_XL1.0/sai-pixelart
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -777,8 +786,8 @@ TUNERS:
    DESCRIPTION:
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-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD2.1/a5ab89c0960be8c1216e65c98d92ae4a.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD2.1/sai-pixelart
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD2.1/a5ab89c0960be8c1216e65c98d92ae4a.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD2.1/sai-pixelart
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
  -
@@ -787,7 +796,7 @@ TUNERS:
    DESCRIPTION:
    SOURCE: sai
    BASE_MODEL: SD1.5
-    IMAGE_PATH: ms://damo/scepter@mantra_images/SD1.5/a5ab89c0960be8c1216e65c98d92ae4a.png
-    MODEL_PATH: ms://damo/scepter_scedit@tuners_model/SD1.5/sai-pixelart
+    IMAGE_PATH: ms://iic/scepter@mantra_images_jpg/SD1.5/a5ab89c0960be8c1216e65c98d92ae4a.jpg
+    MODEL_PATH: ms://iic/scepter_scedit@tuners_model/SD1.5/sai-pixelart
    TUNER_TYPE: SwiftSCE
    PROMPT_EXAMPLE: a boy wearing green jacket
@@ -10,7 +10,7 @@ DESC_INFO:
    <table align="center">
      <tr>
      <td>
-        <img src="https://modelscope.cn/api/v1/models/damo/scepter/repo?Revision=master&FilePath=assets/scepter_studio/scepter_studio_banner.jpg">
+        <img src="https://modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=assets/scepter_studio/scepter_studio_banner.jpg">
        <h3><center>SCEPTER Studio是基于开源基模型和自研微调编辑算法构建的生成定制和编辑工具箱，提供围绕生成、微调、编辑、数据处理等一系列的工具和插件。</center><h3>
      </td>
      </tr>
@@ -22,7 +22,7 @@ DESC_INFO:
    <table align="center">
      <tr>
      <td>
-        <img src="https://modelscope.cn/api/v1/models/damo/scepter/repo?Revision=master&FilePath=assets/scepter_studio/scepter_studio_banner.jpg">
+        <img src="https://modelscope.cn/api/v1/models/iic/scepter/repo?Revision=master&FilePath=assets/scepter_studio/scepter_studio_banner.jpg">
        <h3><center>SCEPTER Studio is a customized generation and editing toolkit built on the open-source base models and proprietary fine-tuning editing algorithms, offering a range of tools and plugins centered around generation, fine-tuning, editing, and data processing.</center><h3>
      </td>
      </tr>
@@ -0,0 +1,151 @@
+NAME: COGVIDEOX_2B
+IS_DEFAULT: False
+DEFAULT_PARAS:
+  PARAS:
+    RESOLUTIONS: [[480, 720]]
+  INPUT:
+    IMAGE:
+    ORIGINAL_SIZE_AS_TUPLE: [480, 720]
+    TARGET_SIZE_AS_TUPLE: [480, 720]
+    PROMPT: ""
+    NEGATIVE_PROMPT: ""
+    PROMPT_PREFIX: ""
+    SAMPLE: ddim
+    SAMPLE_STEPS: 50
+    GUIDE_SCALE: 6.0
+    GUIDE_RESCALE: 0.0
+    DISCRETIZATION: trailing
+    NUM_FRAMES:
+      DEFAULT: 49
+      VISIBLE: True
+    FPS:
+      DEFAULT: 8
+      VISIBLE: True
+  OUTPUT:
+    VIDEOS:
+    SEED:
+  MODULES_PARAS:
+    FIRST_STAGE_MODEL:
+      FUNCTION:
+        -
+          NAME: decode
+          DTYPE: bfloat16
+          INPUT: ["LATENT"]
+      PARAS:
+          SCALING_FACTOR_IMAGE: 1.15258426
+    DIFFUSION_MODEL:
+      FUNCTION:
+        -
+          NAME: forward
+          DTYPE: bfloat16
+          INPUT: ["SAMPLE_STEPS", "SAMPLE", "GUIDE_SCALE", "GUIDE_RESCALE", "DISCRETIZATION", "NUM_FRAMES", "FPS"]
+      PARAS:
+        USE_ROTARY_POSITIONAL_EMBEDDINGS: False
+        PATCH_SIZE: 2
+        LATENT_CHANNELS: 16
+        SCALE_FACTOR_SPATIAL: 8
+        SCALE_FACTOR_TEMPORAL: 4
+        ATTENTION_HEAD_DIM: 64
+        SAMPLE_HEIGHT: 480
+        SAMPLE_WIDTH: 720
+    COND_STAGE_MODEL:
+      FUNCTION:
+        -
+          NAME: encode
+          DTYPE: bfloat16
+          INPUT: ["PROMPT"]
+#
+MODEL:
+  PRETRAINED_MODEL:
+  DIFFUSION:
+    NAME: BaseDiffusion
+    PREDICTION_TYPE: v
+    NOISE_SCHEDULER:
+      NAME: ScaledLinearScheduler
+      BETA_MIN: 0.00085
+      BETA_MAX: 0.012
+      SNR_SHIFT_SCALE: 3.0
+      RESCALE_BETAS_ZERO_SNR: True
+    DIFFUSION_SAMPLERS:
+      NAME: DDIMSampler
+      DISCRETIZATION_TYPE: trailing
+      ETA: 0.0
+  #
+  DIFFUSION_MODEL:
+    NAME: CogVideoXTransformer3DModel
+    DTYPE: bfloat16
+    PRETRAINED_MODEL: ms://AI-ModelScope/CogVideoX-2b@transformer/diffusion_pytorch_model.safetensors
+    NUM_ATTENTION_HEADS: 30
+    ATTENTION_HEAD_DIM: 64
+    IN_CHANNELS: 16
+    OUT_CHANNELS: 16
+    FLIP_SIN_TO_COS: True
+    FREQ_SHIFT: 0
+    TIME_EMBED_DIM: 512
+    TEXT_EMBED_DIM: 4096
+    NUM_LAYERS: 30
+    DROPOUT: 0.0
+    ATTENTION_BIAS: True
+    SAMPLE_WIDTH: 90
+    SAMPLE_HEIGHT: 60
+    SAMPLE_FRAMES: 49
+    PATCH_SIZE: 2
+    TEMPORAL_COMPRESSION_RATIO: 4
+    MAX_TEXT_SEQ_LENGTH: 226
+    ACTIVATION_FN: "gelu-approximate"
+    TIMESTEP_ACTIVATION_FN: "silu"
+    NORM_ELEMENTWISE_AFFINE: True
+    NORM_EPS: 1e-5
+    SPATIAL_INTERPOLATION_SCALE: 1.875
+    TEMPORAL_INTERPOLATION_SCALE: 1.0
+    USE_ROTARY_POSITIONAL_EMBEDDINGS: False
+    USE_LEARNED_POSITIONAL_EMBEDDINGS: False
+    GRADIENT_CHECKPOINTING: False
+  #
+  FIRST_STAGE_MODEL:
+    NAME: AutoencoderKLCogVideoX
+    DTYPE: bfloat16
+    PRETRAINED_MODEL: ms://AI-ModelScope/CogVideoX-2b@vae/diffusion_pytorch_model.safetensors
+    SAMPLE_HEIGHT: 480
+    SAMPLE_WIDTH: 720
+    USE_QUANT_CONV: False
+    USE_POST_QUANT_CONV: False
+    USE_SLICING: True
+    USE_TILING: True
+    GRADIENT_CHECKPOINTING: False
+    ENCODER:
+      NAME: CogVideoXEncoder3D
+      IN_CHANNELS: 3
+      OUT_CHANNELS: 16
+      UP_BLOCK_TYPES: [ "CogVideoXDownBlock3D", "CogVideoXDownBlock3D", "CogVideoXDownBlock3D", "CogVideoXDownBlock3D" ]
+      BLOCK_OUT_CHANNELS: [ 128, 256, 256, 512 ]
+      LAYERS_PER_BLOCK: 3
+      ACT_FN: "silu"
+      NORM_EPS: 1e-6
+      NORM_NUM_GROUPS: 32
+      DROPOUT: 0.0
+      PAD_MODE: "first"
+      TEMPORAL_COMPRESSION_RATIO: 4
+      GRADIENT_CHECKPOINTING: False
+    DECODER:
+      NAME: CogVideoXDecoder3D
+      IN_CHANNELS: 16
+      OUT_CHANNELS: 3
+      UP_BLOCK_TYPES: [ "CogVideoXUpBlock3D", "CogVideoXUpBlock3D", "CogVideoXUpBlock3D", "CogVideoXUpBlock3D" ]
+      BLOCK_OUT_CHANNELS: [ 128, 256, 256, 512 ]
+      LAYERS_PER_BLOCK: 3
+      ACT_FN: "silu"
+      NORM_EPS: 1e-6
+      NORM_NUM_GROUPS: 32
+      DROPOUT: 0.0
+      PAD_MODE: "first"
+      TEMPORAL_COMPRESSION_RATIO: 4
+      GRADIENT_CHECKPOINTING: False
+  #
+  COND_STAGE_MODEL:
+    NAME: T5EmbedderHF
+    PRETRAINED_MODEL: ms://AI-ModelScope/t5-v1_1-xxl
+    TOKENIZER_PATH: ms://AI-ModelScope/t5-v1_1-xxl
+    LENGTH: 226
+    CLEAN:
+    USE_GRAD: False
@@ -0,0 +1,153 @@
+NAME: COGVIDEOX_5B
+IS_DEFAULT: False
+DEFAULT_PARAS:
+  PARAS:
+    RESOLUTIONS: [[480, 720]]
+  INPUT:
+    IMAGE:
+    ORIGINAL_SIZE_AS_TUPLE: [480, 720]
+    TARGET_SIZE_AS_TUPLE: [480, 720]
+    PROMPT: ""
+    NEGATIVE_PROMPT: ""
+    PROMPT_PREFIX: ""
+    SAMPLE: ddim
+    SAMPLE_STEPS: 50
+    GUIDE_SCALE: 6.0
+    GUIDE_RESCALE: 0.0
+    DISCRETIZATION: trailing
+    NUM_FRAMES:
+      DEFAULT: 49
+      VISIBLE: True
+    FPS:
+      DEFAULT: 8
+      VISIBLE: True
+  OUTPUT:
+    VIDEOS:
+    SEED:
+  MODULES_PARAS:
+    FIRST_STAGE_MODEL:
+      FUNCTION:
+        -
+          NAME: decode
+          DTYPE: bfloat16
+          INPUT: ["LATENT"]
+      PARAS:
+          SCALING_FACTOR_IMAGE: 0.7  # 5b diff
+    DIFFUSION_MODEL:
+      FUNCTION:
+        -
+          NAME: forward
+          DTYPE: bfloat16
+          INPUT: ["SAMPLE_STEPS", "SAMPLE", "GUIDE_SCALE", "GUIDE_RESCALE", "DISCRETIZATION", "NUM_FRAMES", "FPS"]
+      PARAS:
+        USE_ROTARY_POSITIONAL_EMBEDDINGS: True
+        PATCH_SIZE: 2
+        LATENT_CHANNELS: 16
+        SCALE_FACTOR_SPATIAL: 8
+        SCALE_FACTOR_TEMPORAL: 4
+        ATTENTION_HEAD_DIM: 64
+        SAMPLE_HEIGHT: 480
+        SAMPLE_WIDTH: 720
+    COND_STAGE_MODEL:
+      FUNCTION:
+        -
+          NAME: encode
+          DTYPE: bfloat16
+          INPUT: ["PROMPT"]
+#
+MODEL:
+  PRETRAINED_MODEL:
+  DIFFUSION:
+    NAME: BaseDiffusion
+    PREDICTION_TYPE: v
+    NOISE_SCHEDULER:
+      NAME: ScaledLinearScheduler
+      BETA_MIN: 0.00085
+      BETA_MAX: 0.012
+      SNR_SHIFT_SCALE: 1.0  # 5b diff
+      RESCALE_BETAS_ZERO_SNR: True
+    DIFFUSION_SAMPLERS:
+      NAME: DDIMSampler
+      DISCRETIZATION_TYPE: trailing
+      ETA: 0.0
+  #
+  DIFFUSION_MODEL:
+    NAME: CogVideoXTransformer3DModel
+    DTYPE: bfloat16
+    PRETRAINED_MODEL: # 5b diff
+      - ms://AI-ModelScope/CogVideoX-5b@transformer/diffusion_pytorch_model-00001-of-00002.safetensors
+      - ms://AI-ModelScope/CogVideoX-5b@transformer/diffusion_pytorch_model-00002-of-00002.safetensors
+    NUM_ATTENTION_HEADS: 48  # 5b diff
+    ATTENTION_HEAD_DIM: 64
+    IN_CHANNELS: 16
+    OUT_CHANNELS: 16
+    FLIP_SIN_TO_COS: True
+    FREQ_SHIFT: 0
+    TIME_EMBED_DIM: 512
+    TEXT_EMBED_DIM: 4096
+    NUM_LAYERS: 42  # 5b diff
+    DROPOUT: 0.0
+    ATTENTION_BIAS: True
+    SAMPLE_WIDTH: 90
+    SAMPLE_HEIGHT: 60
+    SAMPLE_FRAMES: 49
+    PATCH_SIZE: 2
+    TEMPORAL_COMPRESSION_RATIO: 4
+    MAX_TEXT_SEQ_LENGTH: 226
+    ACTIVATION_FN: "gelu-approximate"
+    TIMESTEP_ACTIVATION_FN: "silu"
+    NORM_ELEMENTWISE_AFFINE: True
+    NORM_EPS: 1e-5
+    SPATIAL_INTERPOLATION_SCALE: 1.875
+    TEMPORAL_INTERPOLATION_SCALE: 1.0
+    USE_ROTARY_POSITIONAL_EMBEDDINGS: True # 5b diff
+    USE_LEARNED_POSITIONAL_EMBEDDINGS: False
+    GRADIENT_CHECKPOINTING: True
+  #
+  FIRST_STAGE_MODEL:
+    NAME: AutoencoderKLCogVideoX
+    DTYPE: bfloat16
+    PRETRAINED_MODEL: ms://AI-ModelScope/CogVideoX-5b@vae/diffusion_pytorch_model.safetensors # 5b diff
+    SAMPLE_HEIGHT: 480
+    SAMPLE_WIDTH: 720
+    USE_QUANT_CONV: False
+    USE_POST_QUANT_CONV: False
+    USE_SLICING: True
+    USE_TILING: True
+    GRADIENT_CHECKPOINTING: True
+    ENCODER:
+      NAME: CogVideoXEncoder3D
+      IN_CHANNELS: 3
+      OUT_CHANNELS: 16
+      UP_BLOCK_TYPES: [ "CogVideoXDownBlock3D", "CogVideoXDownBlock3D", "CogVideoXDownBlock3D", "CogVideoXDownBlock3D" ]
+      BLOCK_OUT_CHANNELS: [ 128, 256, 256, 512 ]
+      LAYERS_PER_BLOCK: 3
+      ACT_FN: "silu"
+      NORM_EPS: 1e-6
+      NORM_NUM_GROUPS: 32
+      DROPOUT: 0.0
+      PAD_MODE: "first"
+      TEMPORAL_COMPRESSION_RATIO: 4
+      GRADIENT_CHECKPOINTING: True
+    DECODER:
+      NAME: CogVideoXDecoder3D
+      IN_CHANNELS: 16
+      OUT_CHANNELS: 3
+      UP_BLOCK_TYPES: [ "CogVideoXUpBlock3D", "CogVideoXUpBlock3D", "CogVideoXUpBlock3D", "CogVideoXUpBlock3D" ]
+      BLOCK_OUT_CHANNELS: [ 128, 256, 256, 512 ]
+      LAYERS_PER_BLOCK: 3
+      ACT_FN: "silu"
+      NORM_EPS: 1e-6
+      NORM_NUM_GROUPS: 32
+      DROPOUT: 0.0
+      PAD_MODE: "first"
+      TEMPORAL_COMPRESSION_RATIO: 4
+      GRADIENT_CHECKPOINTING: True
+  #
+  COND_STAGE_MODEL:
+    NAME: T5EmbedderHF
+    PRETRAINED_MODEL: ms://AI-ModelScope/t5-v1_1-xxl
+    TOKENIZER_PATH: ms://AI-ModelScope/t5-v1_1-xxl
+    LENGTH: 226
+    CLEAN:
+    USE_GRAD: False
@@ -0,0 +1,201 @@
+NAME: FLUX1.0_DEV
+IS_DEFAULT: False
+DEFAULT_PARAS:
+  PARAS:
+    RESOLUTIONS: [[1024, 1024]]
+  INPUT:
+    IMAGE:
+    ORIGINAL_SIZE_AS_TUPLE: [1024, 1024]
+    TARGET_SIZE_AS_TUPLE: [1024, 1024]
+    PROMPT: ""
+    NEGATIVE_PROMPT:
+      DEFAULT: ""
+      VISIBLE: False
+    PROMPT_PREFIX: ""
+    SAMPLE:
+      VALUES: ["flow_euler"]
+      DEFAULT: "flow_euler"
+    SAMPLE_STEPS: 50
+    GUIDE_SCALE: 3.5
+    GUIDE_RESCALE:
+      DEFAULT: 0.0
+      VISIBLE: False
+    DISCRETIZATION:
+      VALUES: []
+      DEFAULT:
+      VISIBLE: False
+  OUTPUT:
+    LATENT:
+    IMAGES:
+    SEED:
+  MODULES_PARAS:
+    FIRST_STAGE_MODEL:
+      FUNCTION:
+        -
+          NAME: encode
+          DTYPE: bfloat16
+          INPUT: ["IMAGE"]
+        -
+          NAME: decode
+          DTYPE: bfloat16
+          INPUT: ["LATENT"]
+      PARAS:
+        SCALE_FACTOR: 1.5305
+        SHIFT_FACTOR: 0.0609
+        SIZE_FACTOR: 8
+    DIFFUSION_MODEL:
+      FUNCTION:
+        -
+          NAME: forward
+          DTYPE: bfloat16
+          INPUT: ["SAMPLE_STEPS", "SAMPLE", "GUIDE_SCALE"]
+    COND_STAGE_MODEL:
+      FUNCTION:
+        -
+          NAME: encode
+          DTYPE: bfloat16
+          INPUT: ["PROMPT"]
+#
+MODEL:
+  NAME: LatentDiffusionFlux
+  PARAMETERIZATION: rf
+  TIMESTEPS: 1000
+  MIN_SNR_GAMMA:
+  ZERO_TERMINAL_SNR: False
+  PRETRAINED_MODEL:
+  IGNORE_KEYS: [ ]
+  DEFAULT_N_PROMPT:
+  USE_EMA: False
+  EVAL_EMA: False
+  DIFFUSION:
+    # NAME DESCRIPTION:  TYPE:  default: 'DiffusionFluxRF'
+    NAME: DiffusionFluxRF
+    PREDICTION_TYPE: raw
+    # NOISE_SCHEDULER DESCRIPTION:  TYPE:  default: ''
+    NOISE_SCHEDULER:
+      # NAME DESCRIPTION:  TYPE:  default: 'FlowMatchSigmaScheduler'
+      NAME: FlowMatchSigmaScheduler
+      # WEIGHTING_SCHEME DESCRIPTION: The weighting scheme for sampling timesteps, choose from ['sigma_sqrt', 'logit_normal', 'mode', 'cosmap', 'none']. TYPE: str default: 'logit_normal'
+      WEIGHTING_SCHEME: logit_normal
+      SHIFT: 3.0
+      # LOGIT_MEAN DESCRIPTION: The mean of the logit distribution for sampling timesteps. TYPE: float default: 0.0
+      LOGIT_MEAN: 0.0
+      # LOGIT_STD DESCRIPTION: The standard deviation of the logit distribution for sampling timesteps. TYPE: float default: 1.0
+      LOGIT_STD: 1.0
+      # MODE_SCALE DESCRIPTION: The scale factor for the mode of the logit distribution for sampling timesteps. TYPE: float default: 1.29
+      MODE_SCALE: 1.29
+      #
+  DIFFUSION_MODEL:
+    # NAME DESCRIPTION:  TYPE:  default: 'Flux'
+    NAME: Flux
+    PRETRAINED_MODEL: ms://AI-ModelScope/FLUX.1-dev@flux1-dev.safetensors
+    # IN_CHANNELS DESCRIPTION: model's input channels. TYPE: int default: 64
+    IN_CHANNELS: 64
+    # HIDDEN_SIZE DESCRIPTION: model's hidden size. TYPE: int default: 1024
+    HIDDEN_SIZE: 3072
+    # NUM_HEADS DESCRIPTION: number of heads in the transformer. TYPE: int default: 16
+    NUM_HEADS: 24
+    # AXES_DIM DESCRIPTION: dimensions of the axes of the positional encoding. TYPE: list default: [16, 56, 56]
+    AXES_DIM: [ 16, 56, 56 ]
+    # THETA DESCRIPTION: theta for positional encoding. TYPE: int default: 10000
+    THETA: 10000
+    # VEC_IN_DIM DESCRIPTION: dimension of the vector input. TYPE: int default: 768
+    VEC_IN_DIM: 768
+    # GUIDANCE_EMBED DESCRIPTION: whether to use guidance embedding. TYPE: bool default: False
+    GUIDANCE_EMBED: True
+    # CONTEXT_IN_DIM DESCRIPTION: dimension of the context input. TYPE: int default: 4096
+    CONTEXT_IN_DIM: 4096
+    # MLP_RATIO DESCRIPTION: ratio of mlp hidden size to hidden size. TYPE: float default: 4.0
+    MLP_RATIO: 4.0
+    # QKV_BIAS DESCRIPTION: whether to use bias in qkv projection. TYPE: bool default: True
+    QKV_BIAS: True
+    # DEPTH DESCRIPTION: number of transformer blocks. TYPE: int default: 19
+    DEPTH: 19
+    # DEPTH_SINGLE_BLOCKS DESCRIPTION: number of transformer blocks in the single stream block. TYPE: int default: 38
+    DEPTH_SINGLE_BLOCKS: 38
+
+  #
+  FIRST_STAGE_MODEL:
+    NAME: AutoencoderKLFlux
+    EMBED_DIM: 16
+    PRETRAINED_MODEL: ms://AI-ModelScope/FLUX.1-dev@ae.safetensors
+    IGNORE_KEYS: [ ]
+    BATCH_SIZE: 8
+    USE_CONV: False
+    SCALE_FACTOR: 0.3611
+    SHIFT_FACTOR: 0.1159
+    #
+    ENCODER:
+      NAME: Encoder
+      USE_CHECKPOINT: True
+      CH: 128
+      OUT_CH: 3
+      NUM_RES_BLOCKS: 2
+      IN_CHANNELS: 3
+      ATTN_RESOLUTIONS: [ ]
+      CH_MULT: [ 1, 2, 4, 4 ]
+      Z_CHANNELS: 16
+      DOUBLE_Z: True
+      DROPOUT: 0.0
+      RESAMP_WITH_CONV: True
+    #
+    DECODER:
+      NAME: Decoder
+      USE_CHECKPOINT: True
+      CH: 128
+      OUT_CH: 3
+      NUM_RES_BLOCKS: 2
+      IN_CHANNELS: 3
+      ATTN_RESOLUTIONS: [ ]
+      CH_MULT: [ 1, 2, 4, 4 ]
+      Z_CHANNELS: 16
+      DROPOUT: 0.0
+      RESAMP_WITH_CONV: True
+      GIVE_PRE_END: False
+      TANH_OUT: False
+  #
+  COND_STAGE_MODEL:
+    # NAME DESCRIPTION:  TYPE:  default: 'T5PlusClipFluxEmbedder'
+    NAME: T5PlusClipFluxEmbedder
+    # T5_MODEL DESCRIPTION:  TYPE:  default: ''
+    T5_MODEL:
+      # NAME DESCRIPTION:  TYPE:  default: 'HFEmbedder'
+      NAME: HFEmbedder
+      # HF_MODEL_CLS DESCRIPTION: huggingface cls in transfomer TYPE: NoneType default: None
+      HF_MODEL_CLS: T5EncoderModel
+      # MODEL_PATH DESCRIPTION: model folder path TYPE: NoneType default: None
+      MODEL_PATH: ms://AI-ModelScope/FLUX.1-dev@text_encoder_2/
+      # HF_TOKENIZER_CLS DESCRIPTION: huggingface cls in transfomer TYPE: NoneType default: None
+      HF_TOKENIZER_CLS: T5Tokenizer
+      # TOKENIZER_PATH DESCRIPTION: tokenizer folder path TYPE: NoneType default: None
+      TOKENIZER_PATH: ms://AI-ModelScope/FLUX.1-dev@tokenizer_2/
+      # MAX_LENGTH DESCRIPTION: max length of input TYPE: int default: 77
+      MAX_LENGTH: 512
+      # OUTPUT_KEY DESCRIPTION: output key TYPE: str default: 'last_hidden_state'
+      OUTPUT_KEY: last_hidden_state
+      # D_TYPE DESCRIPTION: dtype TYPE: str default: 'bfloat16'
+      D_TYPE: bfloat16
+      # BATCH_INFER DESCRIPTION: batch infer TYPE: bool default: False
+      BATCH_INFER: False
+      CLEAN: whitespace
+    # CLIP_MODEL DESCRIPTION:  TYPE:  default: ''
+    CLIP_MODEL:
+      # NAME DESCRIPTION:  TYPE:  default: 'HFEmbedder'
+      NAME: HFEmbedder
+      # HF_MODEL_CLS DESCRIPTION: huggingface cls in transfomer TYPE: NoneType default: None
+      HF_MODEL_CLS: CLIPTextModel
+      # MODEL_PATH DESCRIPTION: model folder path TYPE: NoneType default: None
+      MODEL_PATH: ms://AI-ModelScope/FLUX.1-dev@text_encoder/
+      # HF_TOKENIZER_CLS DESCRIPTION: huggingface cls in transfomer TYPE: NoneType default: None
+      HF_TOKENIZER_CLS: CLIPTokenizer
+      # TOKENIZER_PATH DESCRIPTION: tokenizer folder path TYPE: NoneType default: None
+      TOKENIZER_PATH: ms://AI-ModelScope/FLUX.1-dev@tokenizer/
+      # MAX_LENGTH DESCRIPTION: max length of input TYPE: int default: 77
+      MAX_LENGTH: 77
+      # OUTPUT_KEY DESCRIPTION: output key TYPE: str default: 'last_hidden_state'
+      OUTPUT_KEY: pooler_output
+      # D_TYPE DESCRIPTION: dtype TYPE: str default: 'bfloat16'
+      D_TYPE: bfloat16
+      # BATCH_INFER DESCRIPTION: batch infer TYPE: bool default: False
+      BATCH_INFER: True
+      CLEAN: whitespace
@@ -0,0 +1,212 @@
+NAME: FLUX1.0_SCHNELL
+IS_DEFAULT: False
+DEFAULT_PARAS:
+  PARAS:
+    RESOLUTIONS: [[1024, 1024]]
+  INPUT:
+    IMAGE:
+    ORIGINAL_SIZE_AS_TUPLE: [1024, 1024]
+    TARGET_SIZE_AS_TUPLE: [1024, 1024]
+    PROMPT: ""
+    NEGATIVE_PROMPT:
+      DEFAULT: ""
+      VISIBLE: False
+    PROMPT_PREFIX: ""
+    SAMPLE:
+      VALUES: ["flow_euler"]
+      DEFAULT: "flow_euler"
+    SAMPLE_STEPS: 4
+    GUIDE_SCALE: 3.5
+    GUIDE_RESCALE:
+      DEFAULT: 0.0
+      VISIBLE: False
+    DISCRETIZATION:
+      VALUES: []
+      DEFAULT:
+      VISIBLE: False
+  OUTPUT:
+    LATENT:
+    IMAGES:
+    SEED:
+  MODULES_PARAS:
+    FIRST_STAGE_MODEL:
+      FUNCTION:
+        -
+          NAME: encode
+          DTYPE: bfloat16
+          INPUT: ["IMAGE"]
+        -
+          NAME: decode
+          DTYPE: bfloat16
+          INPUT: ["LATENT"]
+      PARAS:
+        SCALE_FACTOR: 1.5305
+        SHIFT_FACTOR: 0.0609
+        SIZE_FACTOR: 8
+    DIFFUSION_MODEL:
+      FUNCTION:
+        -
+          NAME: forward
+          DTYPE: bfloat16
+          INPUT: ["SAMPLE_STEPS", "SAMPLE", "GUIDE_SCALE"]
+    COND_STAGE_MODEL:
+      FUNCTION:
+        -
+          NAME: encode
+          DTYPE: bfloat16
+          INPUT: ["PROMPT"]
+#
+MODEL:
+  NAME: LatentDiffusionFlux
+  PARAMETERIZATION: rf
+  TIMESTEPS: 1000
+  MIN_SNR_GAMMA:
+  ZERO_TERMINAL_SNR: False
+  PRETRAINED_MODEL:
+  IGNORE_KEYS: [ ]
+  DEFAULT_N_PROMPT:
+  USE_EMA: False
+  EVAL_EMA: False
+  DIFFUSION:
+    # NAME DESCRIPTION:  TYPE:  default: 'DiffusionFluxRF'
+    NAME: DiffusionFluxRF
+    PREDICTION_TYPE: raw
+    # NOISE_SCHEDULER DESCRIPTION:  TYPE:  default: ''
+    NOISE_SCHEDULER:
+      # NAME DESCRIPTION:  TYPE:  default: 'FlowMatchSigmaScheduler'
+      NAME: FlowMatchSigmaScheduler
+      # WEIGHTING_SCHEME DESCRIPTION: The weighting scheme for sampling timesteps, choose from ['sigma_sqrt', 'logit_normal', 'mode', 'cosmap', 'none']. TYPE: str default: 'logit_normal'
+      WEIGHTING_SCHEME: logit_normal
+      SHIFT: 3.0
+      # LOGIT_MEAN DESCRIPTION: The mean of the logit distribution for sampling timesteps. TYPE: float default: 0.0
+      LOGIT_MEAN: 0.0
+      # LOGIT_STD DESCRIPTION: The standard deviation of the logit distribution for sampling timesteps. TYPE: float default: 1.0
+      LOGIT_STD: 1.0
+      # MODE_SCALE DESCRIPTION: The scale factor for the mode of the logit distribution for sampling timesteps. TYPE: float default: 1.29
+      MODE_SCALE: 1.29
+    SAMPLER_SCHEDULER:
+      # NAME DESCRIPTION:  TYPE:  default: 'FlowMatchFluxShiftScheduler'
+      NAME: FlowMatchFluxShiftScheduler
+      # SHIFT DESCRIPTION: Use timestamp shift or not, default is True. TYPE: bool default: True
+      SHIFT: False
+      # SIGMOID_SCALE DESCRIPTION: The scale of sigmoid function for sampling timesteps. TYPE: int default: 1
+      SIGMOID_SCALE: 1
+      # BASE_SHIFT DESCRIPTION: The base shift factor for the timestamp. TYPE: float default: 0.5
+      BASE_SHIFT: 0.5
+      # MAX_SHIFT DESCRIPTION: The max shift factor for the timestamp. TYPE: float default: 1.15
+      MAX_SHIFT: 1.15
+      #
+  DIFFUSION_MODEL:
+    # NAME DESCRIPTION:  TYPE:  default: 'Flux'
+    NAME: Flux
+    PRETRAINED_MODEL: ms://AI-ModelScope/FLUX.1-schnell@flux1-schnell.safetensors
+    # IN_CHANNELS DESCRIPTION: model's input channels. TYPE: int default: 64
+    IN_CHANNELS: 64
+    # HIDDEN_SIZE DESCRIPTION: model's hidden size. TYPE: int default: 1024
+    HIDDEN_SIZE: 3072
+    # NUM_HEADS DESCRIPTION: number of heads in the transformer. TYPE: int default: 16
+    NUM_HEADS: 24
+    # AXES_DIM DESCRIPTION: dimensions of the axes of the positional encoding. TYPE: list default: [16, 56, 56]
+    AXES_DIM: [ 16, 56, 56 ]
+    # THETA DESCRIPTION: theta for positional encoding. TYPE: int default: 10000
+    THETA: 10000
+    # VEC_IN_DIM DESCRIPTION: dimension of the vector input. TYPE: int default: 768
+    VEC_IN_DIM: 768
+    # GUIDANCE_EMBED DESCRIPTION: whether to use guidance embedding. TYPE: bool default: False
+    GUIDANCE_EMBED: False
+    # CONTEXT_IN_DIM DESCRIPTION: dimension of the context input. TYPE: int default: 4096
+    CONTEXT_IN_DIM: 4096
+    # MLP_RATIO DESCRIPTION: ratio of mlp hidden size to hidden size. TYPE: float default: 4.0
+    MLP_RATIO: 4.0
+    # QKV_BIAS DESCRIPTION: whether to use bias in qkv projection. TYPE: bool default: True
+    QKV_BIAS: True
+    # DEPTH DESCRIPTION: number of transformer blocks. TYPE: int default: 19
+    DEPTH: 19
+    # DEPTH_SINGLE_BLOCKS DESCRIPTION: number of transformer blocks in the single stream block. TYPE: int default: 38
+    DEPTH_SINGLE_BLOCKS: 38
+
+  #
+  FIRST_STAGE_MODEL:
+    NAME: AutoencoderKLFlux
+    EMBED_DIM: 16
+    PRETRAINED_MODEL: ms://AI-ModelScope/FLUX.1-schnell@ae.safetensors
+    IGNORE_KEYS: [ ]
+    BATCH_SIZE: 8
+    USE_CONV: False
+    SCALE_FACTOR: 0.3611
+    SHIFT_FACTOR: 0.1159
+    #
+    ENCODER:
+      NAME: Encoder
+      USE_CHECKPOINT: True
+      CH: 128
+      OUT_CH: 3
+      NUM_RES_BLOCKS: 2
+      IN_CHANNELS: 3
+      ATTN_RESOLUTIONS: [ ]
+      CH_MULT: [ 1, 2, 4, 4 ]
+      Z_CHANNELS: 16
+      DOUBLE_Z: True
+      DROPOUT: 0.0
+      RESAMP_WITH_CONV: True
+    #
+    DECODER:
+      NAME: Decoder
+      USE_CHECKPOINT: True
+      CH: 128
+      OUT_CH: 3
+      NUM_RES_BLOCKS: 2
+      IN_CHANNELS: 3
+      ATTN_RESOLUTIONS: [ ]
+      CH_MULT: [ 1, 2, 4, 4 ]
+      Z_CHANNELS: 16
+      DROPOUT: 0.0
+      RESAMP_WITH_CONV: True
+      GIVE_PRE_END: False
+      TANH_OUT: False
+  #
+  COND_STAGE_MODEL:
+    # NAME DESCRIPTION:  TYPE:  default: 'T5PlusClipFluxEmbedder'
+    NAME: T5PlusClipFluxEmbedder
+    # T5_MODEL DESCRIPTION:  TYPE:  default: ''
+    T5_MODEL:
+      # NAME DESCRIPTION:  TYPE:  default: 'HFEmbedder'
+      NAME: HFEmbedder
+      # HF_MODEL_CLS DESCRIPTION: huggingface cls in transfomer TYPE: NoneType default: None
+      HF_MODEL_CLS: T5EncoderModel
+      # MODEL_PATH DESCRIPTION: model folder path TYPE: NoneType default: None
+      MODEL_PATH: ms://AI-ModelScope/FLUX.1-schnell@text_encoder_2/
+      # HF_TOKENIZER_CLS DESCRIPTION: huggingface cls in transfomer TYPE: NoneType default: None
+      HF_TOKENIZER_CLS: T5Tokenizer
+      # TOKENIZER_PATH DESCRIPTION: tokenizer folder path TYPE: NoneType default: None
+      TOKENIZER_PATH: ms://AI-ModelScope/FLUX.1-schnell@tokenizer_2/
+      # MAX_LENGTH DESCRIPTION: max length of input TYPE: int default: 77
+      MAX_LENGTH: 256
+      # OUTPUT_KEY DESCRIPTION: output key TYPE: str default: 'last_hidden_state'
+      OUTPUT_KEY: last_hidden_state
+      # D_TYPE DESCRIPTION: dtype TYPE: str default: 'bfloat16'
+      D_TYPE: bfloat16
+      # BATCH_INFER DESCRIPTION: batch infer TYPE: bool default: False
+      BATCH_INFER: False
+      CLEAN: whitespace
+    # CLIP_MODEL DESCRIPTION:  TYPE:  default: ''
+    CLIP_MODEL:
+      # NAME DESCRIPTION:  TYPE:  default: 'HFEmbedder'
+      NAME: HFEmbedder
+      # HF_MODEL_CLS DESCRIPTION: huggingface cls in transfomer TYPE: NoneType default: None
+      HF_MODEL_CLS: CLIPTextModel
+      # MODEL_PATH DESCRIPTION: model folder path TYPE: NoneType default: None
+      MODEL_PATH: ms://AI-ModelScope/FLUX.1-schnell@text_encoder/
+      # HF_TOKENIZER_CLS DESCRIPTION: huggingface cls in transfomer TYPE: NoneType default: None
+      HF_TOKENIZER_CLS: CLIPTokenizer
+      # TOKENIZER_PATH DESCRIPTION: tokenizer folder path TYPE: NoneType default: None
+      TOKENIZER_PATH: ms://AI-ModelScope/FLUX.1-schnell@tokenizer/
+      # MAX_LENGTH DESCRIPTION: max length of input TYPE: int default: 77
+      MAX_LENGTH: 77
+      # OUTPUT_KEY DESCRIPTION: output key TYPE: str default: 'last_hidden_state'
+      OUTPUT_KEY: pooler_output
+      # D_TYPE DESCRIPTION: dtype TYPE: str default: 'bfloat16'
+      D_TYPE: bfloat16
+      # BATCH_INFER DESCRIPTION: batch infer TYPE: bool default: False
+      BATCH_INFER: True
+      CLEAN: whitespace
@@ -0,0 +1,120 @@
+NAME: PIXART_ALPHA
+IS_DEFAULT: False
+DEFAULT_PARAS:
+  PARAS:
+    RESOLUTIONS: [[1024, 1024]]
+  INPUT:
+    IMAGE:
+    ORIGINAL_SIZE_AS_TUPLE: [1024, 1024]
+    TARGET_SIZE_AS_TUPLE: [1024, 1024]
+    PROMPT: ""
+    NEGATIVE_PROMPT: ""
+    PROMPT_PREFIX: ""
+    SAMPLE: ddim
+    SAMPLE_STEPS: 20
+    GUIDE_SCALE: 4.5
+    GUIDE_RESCALE: 0.5
+    DISCRETIZATION: trailing
+  OUTPUT:
+    LATENT:
+    IMAGES:
+    SEED:
+  MODULES_PARAS:
+    FIRST_STAGE_MODEL:
+      FUNCTION:
+        -
+          NAME: encode
+          DTYPE: float32
+          INPUT: ["IMAGE"]
+        -
+          NAME: decode
+          DTYPE: float32
+          INPUT: ["LATENT"]
+      PARAS:
+        SCALE_FACTOR: 0.18215
+        SIZE_FACTOR: 8
+    DIFFUSION_MODEL:
+      FUNCTION:
+        -
+          NAME: forward
+          DTYPE: float16
+          INPUT: ["SAMPLE_STEPS", "SAMPLE", "GUIDE_SCALE", "GUIDE_RESCALE", "DISCRETIZATION"]
+    COND_STAGE_MODEL:
+      FUNCTION:
+        -
+          NAME: encode
+          DTYPE: float32
+          INPUT: ["PROMPT"]
+#
+MODEL:
+  PRETRAINED_MODEL:
+  DECODER_BIAS: 0.5
+  SCHEDULE:
+    PARAMETERIZATION: "eps"
+    TIMESTEPS: 1000
+    ZERO_TERMINAL_SNR: False
+    SCHEDULE_ARGS:
+      "NAME": "linear"
+      "BETA_MIN": 0.0001
+      "BETA_MAX": 0.02
+  #
+  DIFFUSION_MODEL:
+    NAME: PixArt
+    PRETRAINED_MODEL: ms://AI-ModelScope/PixArt-alpha@PixArt-XL-2-1024-MS.pth
+    INPUT_SIZE: 128
+    PATCH_SIZE: 2
+    IN_CHANNELS: 4
+    HIDDEN_SIZE: 1152
+    DEPTH: 28
+    NUM_HEADS: 16
+    MLP_RATIO: 4.0
+    CLASS_DROPOUT_PROB: 0.1
+    PRED_SIGMA: True
+    DROP_PATH: 0.0
+    WINDOW_DIZE: 0
+    USE_REL_POS: False
+    CAPTION_CHANNELS: 4096
+    LEWEI_SCALE: 2
+    MODEL_MAX_LENGTH: 120
+  #
+  FIRST_STAGE_MODEL:
+    NAME: AutoencoderKL
+    PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-2-base@512-base-ema.safetensors
+    EMBED_DIM: 4
+    IGNORE_KEYS: [ ]
+    BATCH_SIZE: 1
+    #
+    ENCODER:
+      NAME: Encoder
+      CH: 128
+      OUT_CH: 3
+      NUM_RES_BLOCKS: 2
+      IN_CHANNELS: 3
+      ATTN_RESOLUTIONS: [ ]
+      CH_MULT: [ 1, 2, 4, 4 ]
+      Z_CHANNELS: 4
+      DOUBLE_Z: True
+      DROPOUT: 0.0
+      RESAMP_WITH_CONV: True
+    #
+    DECODER:
+      NAME: Decoder
+      CH: 128
+      OUT_CH: 3
+      NUM_RES_BLOCKS: 2
+      IN_CHANNELS: 3
+      ATTN_RESOLUTIONS: [ ]
+      CH_MULT: [ 1, 2, 4, 4 ]
+      Z_CHANNELS: 4
+      DROPOUT: 0.0
+      RESAMP_WITH_CONV: True
+      GIVE_PRE_END: False
+      TANH_OUT: False
+  #
+  COND_STAGE_MODEL:
+    NAME: T5EmbedderHF
+    PRETRAINED_MODEL: ms://AI-ModelScope/PixArt-alpha@t5-v1_1-xxl/
+    TOKENIZER_PATH: ms://AI-ModelScope/PixArt-alpha@t5-v1_1-xxl/
+    LENGTH: 120
+    CLEAN: heavy
+    USE_GRAD: False
@@ -0,0 +1,148 @@
+NAME: SD3
+IS_DEFAULT: False
+DEFAULT_PARAS:
+  PARAS:
+    RESOLUTIONS: [[1024, 1024]]
+  INPUT:
+    IMAGE:
+    ORIGINAL_SIZE_AS_TUPLE: [1024, 1024]
+    TARGET_SIZE_AS_TUPLE: [1024, 1024]
+    PROMPT: ""
+    NEGATIVE_PROMPT: ""
+    PROMPT_PREFIX: ""
+    SAMPLE: euler
+    SAMPLE_STEPS: 28
+    GUIDE_SCALE: 5.0
+    GUIDE_RESCALE: 0.0
+    DISCRETIZATION: trailing
+  OUTPUT:
+    LATENT:
+    IMAGES:
+    SEED:
+  MODULES_PARAS:
+    FIRST_STAGE_MODEL:
+      FUNCTION:
+        -
+          NAME: encode
+          DTYPE: float32
+          INPUT: ["IMAGE"]
+        -
+          NAME: decode
+          DTYPE: float32
+          INPUT: ["LATENT"]
+      PARAS:
+        SCALE_FACTOR: 1.5305
+        SHIFT_FACTOR: 0.0609
+        SIZE_FACTOR: 8
+    DIFFUSION_MODEL:
+      FUNCTION:
+        -
+          NAME: forward
+          DTYPE: float16
+          INPUT: ["SAMPLE_STEPS", "SAMPLE", "GUIDE_SCALE", "GUIDE_RESCALE", "DISCRETIZATION"]
+    COND_STAGE_MODEL:
+      FUNCTION:
+        -
+          NAME: encode
+          DTYPE: float32
+          INPUT: ["PROMPT"]
+#
+MODEL:
+  PRETRAINED_MODEL:
+  SCHEDULE:
+    PARAMETERIZATION: rf
+    TIMESTEPS: 1000
+    MIN_SNR_GAMMA:
+    ZERO_TERMINAL_SNR: False
+    PRETRAINED_MODEL:
+    IGNORE_KEYS: [ ]
+    SCALE_FACTOR: 1.5305
+    SHIFT_FACTOR: 0.0609
+    DEFAULT_N_PROMPT:
+    SCHEDULE_ARGS:
+      "NAME": "shifted"
+      "SHIFT": 3
+    T_WEIGHT: uniform
+  #
+  DIFFUSION_MODEL:
+    NAME: MMDiT
+    PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium@sd3_medium.safetensors
+    IGNORE_KEYS: '^first_stage_model.'
+    IN_CHANNELS: 16
+    PATCH_SIZE: 2
+    OUT_CHANNELS: 16
+    DEPTH: 24
+    INPUT_SIZE:
+    ADM_IN_CHANNELS: 2048
+    CONTEXT_EMBEDDER_CONFIG: { 'target': 'torch.nn.Linear', 'params': { 'in_features': 4096, 'out_features': 1536 } }
+    NUM_PATCHES: 36864
+    POS_EMBED_MAX_SIZE: 192
+    POS_EMBED_SCALING_FACTOR:
+    USE_CHECKPOINT: True
+  #
+  FIRST_STAGE_MODEL:
+    NAME: AutoencoderKL
+    PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium@sd3_medium.safetensors
+    EMBED_DIM: 16
+    IGNORE_KEYS: '^model.diffusion_model.'
+    BATCH_SIZE: 1
+    USE_CONV: False
+    #
+    ENCODER:
+      NAME: Encoder
+      CH: 128
+      OUT_CH: 3
+      NUM_RES_BLOCKS: 2
+      IN_CHANNELS: 3
+      ATTN_RESOLUTIONS: [ ]
+      CH_MULT: [ 1, 2, 4, 4 ]
+      Z_CHANNELS: 16
+      DOUBLE_Z: True
+      DROPOUT: 0.0
+      RESAMP_WITH_CONV: True
+    #
+    DECODER:
+      NAME: Decoder
+      CH: 128
+      OUT_CH: 3
+      NUM_RES_BLOCKS: 2
+      IN_CHANNELS: 3
+      ATTN_RESOLUTIONS: [ ]
+      CH_MULT: [ 1, 2, 4, 4 ]
+      Z_CHANNELS: 16
+      DROPOUT: 0.0
+      RESAMP_WITH_CONV: True
+      GIVE_PRE_END: False
+      TANH_OUT: False
+  #
+  COND_STAGE_MODEL:
+    NAME: SD3TextEmbedder
+    P_ZERO: 0.0
+    CLIP_L:
+      NAME: FrozenCLIPEmbedder2
+      PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@text_encoder
+      TOKENIZER_PATH: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@tokenizer
+      MAX_LENGTH: 77
+      FREEZE: True
+      LAYER: penultimate
+      RETURN_POOLED: True
+      USE_FINAL_LAYER_NORM: False
+      IS_TRAINABLE: False
+    CLIP_G:
+      NAME: FrozenCLIPEmbedder2
+      PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@text_encoder_2
+      TOKENIZER_PATH: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@tokenizer_2
+      MAX_LENGTH: 77
+      FREEZE: True
+      LAYER: penultimate
+      RETURN_POOLED: True
+      USE_FINAL_LAYER_NORM: False
+      IS_TRAINABLE: False
+    T5_XXL:
+      NAME: T5EmbedderHF
+      PRETRAINED_MODEL: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@text_encoder_3
+      TOKENIZER_PATH: ms://AI-ModelScope/stable-diffusion-3-medium-diffusers@tokenizer_3
+      LENGTH: 256
+      CLEAN: whitespace
+      USE_GRAD: False
+      T5_DTYPE: float16
@@ -2,7 +2,7 @@ NAME: EDIT
 IS_DEFAULT: False
 DEFAULT_PARAS:
  PARAS:
-    RESOLUTIONS: [[1024, 1024]]
+    RESOLUTIONS: [[512, 512], [1024, 1024]]
  INPUT:
    IMAGE:
    PROMPT: ""
@@ -49,7 +49,7 @@ DEFAULT_PARAS:
          INPUT: ["PROMPT", "NEGATIVE_PROMPT"]

 MODEL:
-  PRETRAINED_MODEL: ms://damo/stylebooth@models/stylebooth-tb-5000-0.bin
+  PRETRAINED_MODEL: ms://iic/stylebooth@models/stylebooth-tb-5000-0.bin
  SCHEDULE:
    PARAMETERIZATION: "eps"
    TIMESTEPS: 1000
@@ -6,64 +6,91 @@ DIFFUSION_PARAS:
             'dpm2_karras', 'dpm2_ancestral_karras', 'dpmpp_2s_ancestral_karras', 'dpmpp_2m_karras',
             'dpmpp_sde_karras', 'dpmpp_2m_sde_karras']
    DEFAULT: 'dpmpp_2s_ancestral'
+    VISIBLE: True
  NEGATIVE_PROMPT:
    DEFAULT:
+    VISIBLE: True
  PROMPT_PREFIX:
    DEFAULT:
+    VISIBLE: True
  SAMPLES:
    MIN: 1
    MAX: 4
    DEFAULT: 1
+    VISIBLE: True
+  NUM_FRAMES:
+    MIN: 1
+    MAX: 100
+    DEFAULT: 49
+    VISIBLE: False
+  FPS:
+    MIN: 1
+    MAX: 50
+    DEFAULT: 8
+    VISIBLE: False
  SAMPLE_STEPS:
    MIN: 1
    MAX: 100
    DEFAULT: 30
+    VISIBLE: True
  GUIDE_SCALE:
    MIN: 0
    MAX: 10
    DEFAULT: 5.0
+    VISIBLE: True
  GUIDE_RESCALE:
    MIN: 0
    MAX: 1.0
    DEFAULT: 0.5
+    VISIBLE: True
  DISCRETIZATION:
    VALUES: ["trailing", "leading", "linspace"]
    DEFAULT: "linspace"
+    VISIBLE: True
  REFINE_SAMPLERS:
    VALUES: [ 'ddim', 'euler', 'euler_ancestral', 'heun', 'dpm2',
              'dpm2_ancestral', 'dpmpp_2m', 'dpmpp_sde', 'dpmpp_2m_sde', 'dpmpp_2s_ancestral',
              'dpm2_karras', 'dpm2_ancestral_karras', 'dpmpp_2s_ancestral_karras', 'dpmpp_2m_karras',
              'dpmpp_sde_karras', 'dpmpp_2m_sde_karras' ]
    DEFAULT: 'dpmpp_2s_ancestral'
+    VISIBLE: True
  REFINE_SAMPLE_STEPS:
    MIN: 0
    MAX: 100
    DEFAULT: 30
+    VISIBLE: True
  REFINE_GUIDE_SCALE:
    MIN: 0
    MAX: 10
    DEFAULT: 5.0
+    VISIBLE: True
  REFINE_GUIDE_RESCALE:
    MIN: 0
    MAX: 1.0
    DEFAULT: 0.5
+    VISIBLE: True
  REFINE_DISCRETIZATION:
    VALUES: [ "trailing", "leading", "linspace" ]
    DEFAULT: "linspace"
+    VISIBLE: True
  AESTHETIC_SCORE:
    MIN: 0.0
    MAX: 10.0
    DEFAULT: 6.0
+    VISIBLE: True
  NEGATIVE_AESTHETIC_SCORE:
    MIN: 0.0
    MAX: 10.0
    DEFAULT: 2.5
+    VISIBLE: True
  REFINE_STRENGTH:
    MIN: 0
    MAX: 1.0
    DEFAULT: 0.15
  RESOLUTIONS:
-    VALUES: [[704, 1408], [704, 1344], [768, 1344],
+    VALUES: [
+             [512, 512], [768, 768],
+             [704, 1408], [704, 1344], [768, 1344],
             [720, 1280],
             [768, 1280], [832, 1216], [832, 1152],
             [896, 1152], [896, 1088], [960, 1088],
@@ -73,8 +100,14 @@ DIFFUSION_PARAS:
             [1280, 768],
             [1344, 768], [1344, 704], [1408, 704],
             [1472, 704], [1536, 640], [1600, 640],
-             [1664, 576], [1728, 576]]
+             [1664, 576], [1728, 576],
+             [2048, 2048], [2048, 1920], [1920, 2048],
+             [1536, 2560], [2560, 1536], [2560, 1440],
+             [2560, 1440],
+             [480, 720], [720, 480]
+            ]
    DEFAULT: [1024, 1024]
+    VISIBLE: True
 EXTENSION_PARAS:
  MANTRA_BOOK: scepter/methods/studio/extensions/mantra_book/mantra_book.yaml
  OFFICIAL_TUNERS: scepter/methods/studio/extensions/tuners/official_tuners.yaml
@@ -87,18 +120,18 @@ CONTROLABLE_ANNOTATORS:
    IS_DEFAULT: True
  -
    NAME: "HedAnnotator"
-    PRETRAINED_MODEL: "ms://damo/scepter_scedit@annotator/ckpts/ControlNetHED.pth"
+    PRETRAINED_MODEL: "ms://iic/scepter_scedit@annotator/ckpts/ControlNetHED.pth"
    TYPE: Hed
    IS_DEFAULT: False
  -
    NAME: "OpenposeAnnotator"
-    BODY_MODEL_PATH: "ms://damo/scepter_scedit@annotator/ckpts/body_pose_model.pth"
-    HAND_MODEL_PATH: "ms://damo/scepter_scedit@annotator/ckpts/hand_pose_model.pth"
+    BODY_MODEL_PATH: "ms://iic/scepter_scedit@annotator/ckpts/body_pose_model.pth"
+    HAND_MODEL_PATH: "ms://iic/scepter_scedit@annotator/ckpts/hand_pose_model.pth"
    TYPE: Openpose
    IS_DEFAULT: False
  -
    NAME: "MidasDetector"
-    PRETRAINED_MODEL: "ms://damo/scepter_scedit@annotator/ckpts/dpt_hybrid-midas-501f0c75.pt"
+    PRETRAINED_MODEL: "ms://iic/scepter_scedit@annotator/ckpts/dpt_hybrid-midas-501f0c75.pt"
    TYPE: Midas
    IS_DEFAULT: False
  -
@@ -68,7 +68,7 @@ DEFAULT_PARAS:
          INPUT: ["ORIGINAL_SIZE_AS_TUPLE", "AESTHETIC_SCORE", "NEGATIVE_AESTHETIC_SCORE", "CROP_COORDS_TOP_LEFT", "PROMPT", "NEGATIVE_PROMPT"]

 MODEL:
-  PRETRAINED_MODEL: ms://damo/LARGEN@models/largen_ckpt_s22k.pth
+  PRETRAINED_MODEL: ms://iic/LARGEN@models/largen_ckpt_s22k.pth
  # SCHEDULE_ARGS DESCRIPTION:  TYPE:  default: ''
  SCHEDULE:
    PARAMETERIZATION: "eps"
@@ -245,8 +245,8 @@ MODEL:
        LEGACY_UCG_VALUE:
      -
        NAME: IPAdapterPlusEmbedder
-        CLIP_DIR: ms://damo/LARGEN@models/clip_encoder/
-        PRETRAINED_MODEL: ms://damo/LARGEN@models/ip-adapter-plus_sdxl_vit-h.bin
+        CLIP_DIR: ms://iic/LARGEN@models/clip_encoder/
+        PRETRAINED_MODEL: ms://iic/LARGEN@models/ip-adapter-plus_sdxl_vit-h.bin
        INPUT_KEYS: [ "ref_ip", "ref_detail" ]
        IN_DIM: 1280
        HEADS: 20
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
皓童	af5cf1ccc0	modify edit	2024-12-08 00:31:50 +08:00
皓童	0ed54e05e4	modify edit	2024-12-08 00:28:11 +08:00
皓童	27a2b7833f	modify edit	2024-12-08 00:22:43 +08:00
皓童	6c8ce55888	modify edit	2024-12-08 00:16:03 +08:00
皓童	448cdba522	add init file for chatbot	2024-12-05 15:20:00 +08:00
皓童	2a29446d45	modify ace inference and ace yaml	2024-11-25 14:24:54 +08:00
maochaojie	cd33b4ab15	Merge branch 'v1.3.0_dev' of https://github.com/modelscope/scepter into v1.3.0_dev	2024-11-21 15:42:05 +08:00
maochaojie	7d7943fed3	modify yaml and workflow	2024-11-21 15:41:45 +08:00
jiangzeyinzi	d48b2f110f	Merge pull request #63 from yaosheng216/patch-5 Update model_node.py	2024-11-20 13:26:33 +08:00
Great	82486adf38	Update model_node.py	2024-11-20 13:24:28 +08:00
maochaojie	a683061c6f	upgrade from 1.2.0 to 1.3.0	2024-11-19 19:20:02 +08:00
mcj	4ec0492897	Merge pull request #62 from modelscope/v1.2.0_dev update chatbot example	2024-11-07 20:30:51 +08:00
LouieStark	aac85fa94f	update readme	2024-11-05 19:44:54 +08:00
LouieStark	3f267aaea2	update example	2024-11-05 15:49:00 +08:00
LouieStark	53357f95d6	update chatbot example	2024-11-05 14:36:52 +08:00
mcj	02c0ba9757	Merge pull request #61 from modelscope/v1.2.0_dev update instr	2024-11-04 17:14:27 +08:00
LouieStark	cef93bdbfe	update instr	2024-11-04 16:23:19 +08:00
jiangzeyinzi	82132ff3a1	Merge pull request #60 from modelscope/v1.2.0_dev add instruction	2024-11-04 14:38:03 +08:00
LouieStark	b886400e06	add instruction	2024-11-04 14:34:07 +08:00
mcj	73984c4f9e	Merge pull request #59 from modelscope/v1.2.0_dev update readme	2024-11-02 06:48:03 +08:00
LouieStark	f98adabeb3	update readme	2024-11-01 23:32:28 +08:00
jiangzeyinzi	edb46a615c	Merge pull request #58 from modelscope/v1.2.0_dev V1.2.0 dev	2024-11-01 21:30:20 +08:00
LouieStark	fe3e11b49e	update chatbot	2024-11-01 21:13:21 +08:00
LouieStark	e6b43f19f6	update chatbot	2024-11-01 17:10:56 +08:00
jiangzeyinzi	d9b207cf5b	Merge pull request #55 from modelscope/v1.2.0_dev V1.2.0 dev	2024-11-01 16:53:16 +08:00
LouieStark	986349deac	fix chatbot bug	2024-11-01 16:38:46 +08:00
LouieStark	3f047be43c	update readme and yaml	2024-11-01 11:37:53 +08:00
LouieStark	e8d8e63cba	update v1.2.0	2024-11-01 10:15:27 +08:00
jiangzeyinzi	eac03e9856	Merge pull request #52 from modelscope/v1.1.0_dev update v1.1.0	2024-10-23 10:19:29 +08:00
jiangzeyinzi	379b94ab4f	update	2024-10-23 10:15:31 +08:00
jiangzeyinzi	342c6b8a15	Merge branch 'v1.1.0_dev' of https://github.com/modelscope/scepter into v1.1.0_dev	2024-10-21 11:59:55 +08:00
jiangzeyinzi	4ddcb08c7b	update	2024-10-21 11:59:41 +08:00
jiangzeyinzi	b2169a1597	Update readme.md	2024-10-21 11:58:43 +08:00
jiangzeyinzi	cffd54a02a	update	2024-10-21 11:36:02 +08:00
zeyinzi.jzyz	0bba2c319d	update v1.1.0	2024-10-21 00:35:53 +08:00
LouieStark	7d6451efad	update project page url	2024-10-01 23:45:22 +08:00
LouieStark	a5decd17aa	update readme	2024-09-30 14:22:14 +08:00
jiangzeyinzi	8a14866562	Merge pull request #46 from yaosheng216/patch-4 Update ldm_sce.py	2024-09-27 09:49:27 +08:00
jiangzeyinzi	5a94f6c4a2	Merge pull request #45 from yaosheng216/patch-3 Update sd15_512_sce_ctr_hed.yaml	2024-09-27 09:48:43 +08:00
Great	4ad0f6038c	Update ldm_sce.py	2024-09-27 09:39:22 +08:00
Great	4f56623627	Update sd15_512_sce_ctr_hed.yaml	2024-09-27 09:36:27 +08:00
jiangzeyinzi	30afc0a1de	Merge pull request #39 from yaosheng216/patch-2 Update readme.md	2024-07-18 17:51:53 +08:00
Great	aeabef75b4	Update readme.md	2024-07-18 17:40:28 +08:00
jiangzeyinzi	9376149415	Merge pull request #38 from modelscope/v1.0.3_dev v1.0.3	2024-07-18 17:31:44 +08:00
zeyinzi.jzyz	01fd8335af	v1.0.3 update	2024-07-18 14:12:42 +08:00
Zhen Han	7a9f90efb2	Update stylebooth.md	2024-07-14 20:10:10 +08:00
Zhen Han	cbbef4a2da	Update stylebooth.md	2024-07-14 19:53:11 +08:00
hanzhen.hz	b242449b25	v1.0.2	2024-06-05 16:12:05 +08:00
jiangzeyinzi	2fb8fd1872	Merge pull request #34 from modelscope/v1.0.0_dev v1.0.0 update	2024-06-03 17:49:47 +08:00
jiangzeyinzi	ef82a32944	Update process_watcher.py	2024-06-03 17:47:55 +08:00
hanzhn	aa7e959330	v1.0.0 update	2024-05-31 14:05:54 +08:00
hanzhn	edff6352d5	v1.0.0 update	2024-05-29 13:17:03 +08:00
hanzhn	aa8250e5d2	v1.0.0 update	2024-05-29 10:30:04 +08:00
hanzhn	e7255aac25	v1.0.0 update	2024-05-27 17:12:57 +08:00
Zhen Han	b752ff1cbc	Update readme.md	2024-05-27 14:01:28 +08:00
Zhen Han	8b08629bd0	Update readme.md	2024-05-27 13:28:27 +08:00
hanzhn	c70ef0fc47	v1.0.0 update	2024-05-27 13:15:48 +08:00
Zhen Han	8076aae7da	Merge pull request #28 from modelscope/v0.0.5_dev V0.0.5 dev	2024-04-29 16:54:18 +08:00