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- ---
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- license: cc-by-nc-sa-4.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ base_model:
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+ - gdhe17/Self-Forcing
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+ base_model_relation: quantized
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+ library_name: gguf
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+ tags:
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+ - text-to-video
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+ - image-to-video
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+ - video-to-video
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+ - quantized
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+ language:
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+ - en
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+ license: cc-by-nc-sa-4.0
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+ ---
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+
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+ This is a GGUF conversion of an addon of [gdhe17/Self-Forcing](https://huggingface.co/gdhe17/Self-Forcing) and [Wan-AI/Wan2.1-VACE-1.3B](https://huggingface.co/Wan-AI/Wan2.1-VACE-1.3B) scopes.
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+ The process involved extracting VACE scopes and injecting into the target models, using scripts provided by [wsbagnsv1](https://huggingface.co/wsbagnsv1).
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+ All quantized versions were created from the FP16 model using the conversion scripts provided by city96, available at the [ComfyUI-GGUF](https://github.com/city96/ComfyUI-GGUF/tree/main/tools) GitHub repository.
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+
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+
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+ ## Usage
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+ The model files can be used in [ComfyUI](https://github.com/comfyanonymous/ComfyUI/) with the [ComfyUI-GGUF](https://github.com/city96/ComfyUI-GGUF) custom node. Place the required model(s) in the following folders:
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+
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+ | Type | Name | Location | Download |
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+ | ------------ | -------------------------------------------------- | ------------------------------ | ---------------- |
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+ | Main Model | lym00/Wan2.1_T2V_1.3B_SelfForcing_VACE-GGUF | `ComfyUI/models/unet` | GGUF (this repo) |
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+ | Text Encoder | umt5-xxl-encoder | `ComfyUI/models/text_encoders` | [Safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/tree/main/split_files/text_encoders) / [GGUF](https://huggingface.co/city96/umt5-xxl-encoder-gguf/tree/main) |
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+ | VAE | Wan2_1_VAE_bf16 | `ComfyUI/models/vae` | [Safetensors](https://huggingface.co/Kijai/WanVideo_comfy/blob/main/Wan2_1_VAE_bf16.safetensors) |
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+ [**ComfyUI example workflow**](https://docs.comfy.org/tutorials/video/wan/vace)
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+
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+ ### Notes
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+
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+ *All original licenses and restrictions from the base models still apply.*
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+
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+ ## Reference
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+
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+ - For an overview of quantization types, please see the [GGUF quantization types](https://huggingface.co/docs/hub/gguf#quantization-types).