1 line
20 KiB
JSON
1 line
20 KiB
JSON
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same model type you run in your regular Wan generation workflow.\n- *The key to success and no OOM is to configure this workflow as close to your regular Wan workflow as possible.*\n## If you need GGUF models, replace these nodes with your favorite GGUF loaders. \n"],"color":"#233","bgcolor":"#355"},{"id":38,"type":"MarkdownNote","pos":[-4720,1730],"size":[340,420],"flags":{"collapsed":false},"order":2,"mode":0,"inputs":[],"outputs":[],"title":"Model links","properties":{},"widgets_values":["# VACE Model download links\n\nYou need one of the VACE variants below to run this workflow. Choose the model format and quantization that most closely matches what you run for your regular Wan workflow.\n\n**Wan 2.2 Fun VACE**\n - [bf16 and fp8](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/tree/main/split_files/diffusion_models)\n - [GGUF](https://huggingface.co/QuantStack/Wan2.2-VACE-Fun-A14B-GGUF/tree/main)\n\n**Wan 2.1 VACE**\n\n - [fp16](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/diffusion_models/wan2.1_vace_14B_fp16.safetensors)\n\n - [GGUF](https://huggingface.co/QuantStack/Wan2.1_14B_VACE-GGUF/tree/main)\n\n**Kijai’s extracted Fun Vace 2.2 modules, for loading along with standard T2V models. [Native use examples here.](https://huggingface.co/Kijai/WanVideo_comfy/discussions/81)**\n\n - [bf16](https://huggingface.co/Kijai/WanVideo_comfy/tree/main/Fun/VACE)\n - [GGUF](https://huggingface.co/Kijai/WanVideo_comfy_GGUF/tree/main/VACE)\n\n\n\nModel Storage Location\n\n```\n📂 ComfyUI/\n├── 📂 models/\n│ └── 📂 diffusion_models/\n│ │ ├── wan2.2_fun_vace_high_noise_14B_fp8_scaled.safetensors\n│ │ └── wan2.2_fun_vace_low_noise_14B_fp8_scaled.safetensors\n```\n"],"color":"#432","bgcolor":"#653"},{"id":5,"type":"CLIPTextEncode","pos":[-4200,1850],"size":[210,88],"flags":{"collapsed":false},"order":11,"mode":0,"inputs":[{"localized_name":"clip","name":"clip","type":"CLIP","link":6},{"localized_name":"text","name":"text","type":"STRING","widget":{"name":"text"},"link":null}],"outputs":[{"localized_name":"CONDITIONING","name":"CONDITIONING","type":"CONDITIONING","links":[5]}],"title":"CLIP Text Encode","properties":{"Node name for 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Useful for joining a large number of clips automatically. It also offers some methods for mitigating color/brightness shift that VACE can sometimes introduce.*\n\n---\n\n# How to Use This Workflow\n\n## 1. Install my [*ComfyUI-Wan-VACE-Prep*](https://github.com/stuttlepress/ComfyUI-Wan-VACE-Prep) nodes.\nIf you don't already have the nodes, you can open the Manager and install either from the *Missing* section, or search for **\"Wan VACE Prep\"**.\n\nIt's a tiny package with no dependencies, so it is very unlikely to break your system, if you worry about such things. \n\n\n## 2. Select models appropriate for your system\n- **Select your VACE models** in the *Load* group. Choose models that match what you usually run in your normal Wan workflow. If you usually run FP8 for video generation, choose FP8 VACE models. If you usually use Q4 GGUF, use Q4 GGUF VACE models.\n- **Select or disable lightx2v loras.** Using the same loras and strength that your input clips were generated with may reduce VACE brightness/color artifacts.\n\n## 3. Load your input video\n\n - **3.5 (Optional) Configure the video transition**. \nSet the *extend_from_idx*, *context_frames*, and *new_frames* parameters on the **Wan VACE Extend** node. The defaults work well for 81 frame 16fps clips, but feel free to experiment. Tooltips and the [README file](https://github.com/stuttlepress/ComfyUI-Wan-VACE-Prep/blob/main/README.md#wan-vace-extend) give a little more information about how the parameters work.\n\n## 4. 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