Add README files and requirements
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# ComfyUI_RH_mammothmoda
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ComfyUI custom nodes for MammothModa2 text-to-image generation.
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## Features
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- **Text-to-Image Generation**: High-quality image synthesis using MammothModa2
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- **Optimized Performance**: INT8 quantization support for efficient inference
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- **Flash Attention**: Enhanced speed with flash_attention_2
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## Installation
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### Via ComfyUI Manager (Recommended)
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Search for "RunningHub Mammothmoda" in ComfyUI Manager and install.
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### Manual Installation
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```bash
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cd ComfyUI/custom_nodes
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git clone https://github.com/HM-RunningHub/ComfyUI_RH_mammothmoda.git
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cd ComfyUI_RH_mammothmoda
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pip install -r requirements.txt
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```
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## Model Download
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Download the MammothModa2-Preview model and place it in:
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```
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ComfyUI/models/MammothModa2-Preview/
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```
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Model source: Check official MammothModa2 repository for model weights.
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## Usage
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1. **Load Model**: Use "RunningHub Mammothmoda Loader" node
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2. **Generate Image**: Connect to "RunningHub Mammothmoda T2I Sampler" node
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3. **Configure**: Set prompt, size (width/height), steps, and guidance scales
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4. **Run**: Execute workflow to generate images
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## Nodes
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- **RunningHub Mammothmoda Loader**: Loads the MammothModa2 model
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- **RunningHub Mammothmoda T2I Sampler**: Generates images from text prompts
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## Requirements
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- CUDA-capable GPU (24GB VRAM recommended)
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- PyTorch with CUDA support
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- flash-attn package
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## License
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See LICENSE file for details.
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# ComfyUI_RH_mammothmoda
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ComfyUI 自定义节点,用于 MammothModa2 文本生成图像。
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## 功能特点
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- **文本生成图像**:使用 MammothModa2 进行高质量图像合成
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- **性能优化**:支持 INT8 量化实现高效推理
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- **Flash Attention**:使用 flash_attention_2 加速
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## 安装方法
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### 通过 ComfyUI Manager 安装(推荐)
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在 ComfyUI Manager 中搜索 "RunningHub Mammothmoda" 并安装。
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### 手动安装
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```bash
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cd ComfyUI/custom_nodes
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git clone https://github.com/HM-RunningHub/ComfyUI_RH_mammothmoda.git
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cd ComfyUI_RH_mammothmoda
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pip install -r requirements.txt
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```
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## 模型下载
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下载 MammothModa2-Preview 模型并放置到:
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```
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ComfyUI/models/MammothModa2-Preview/
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```
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模型来源:请查看 MammothModa2 官方仓库获取模型权重。
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## 使用说明
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1. **加载模型**:使用 "RunningHub Mammothmoda Loader" 节点
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2. **生成图像**:连接到 "RunningHub Mammothmoda T2I Sampler" 节点
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3. **配置参数**:设置提示词、尺寸(宽度/高度)、步数和引导比例
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4. **运行**:执行工作流生成图像
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## 节点说明
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- **RunningHub Mammothmoda Loader**:加载 MammothModa2 模型
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- **RunningHub Mammothmoda T2I Sampler**:从文本提示词生成图像
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## 系统要求
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- 支持 CUDA 的 GPU(推荐 24GB 显存)
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- PyTorch(支持 CUDA)
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- flash-attn 包
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## 许可证
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详见 LICENSE 文件。
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torch>=2.0.0
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transformers>=4.40.0
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optimum-quanto
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qwen-vl-utils
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flash-attn>=2.0.0
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pillow
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numpy
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