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WindstormLabs/wan22-encoders
wan22-encoders is a machine learning model from WindstormLabs. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
Organization: WindstormLabs Used by: SceneMachine
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Updated Oct 1, 2026
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From the Hugging Face model README
Organization: WindstormLabs
Used by: SceneMachine
SceneMachine is a sub-project of Windstorm Labs. This repo hosts shared AI/ML infrastructure used by SceneMachine and reusable by future Windstorm Labs sub-projects.
Shared encoder weights used across the Wan 2.2 T2V / I2V / Animate stacks. Wan 2.1 VAE (still used by 2.2), UMT5-xxl text encoder, SigLIP vision-patch14-384 (for I2V), and CLIP-ViT-H (REQUIRED by Animate's face_adapter — SigLIP triggers a LayerNorm shape mismatch).
Primary distribution: https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged + https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged (CLIP-ViT-H)
This repo is a mirror. License terms of the upstream apply unchanged.
Primary license owner(s): Alibaba / Google T5 / Google SigLIP / OpenCLIP-laion
| Filename | Size |
|---|---|
umt5_xxl_bf16_from_pth.safetensors | 11.36 GB |
clip_vision_h.safetensors | 1.26 GB |
sigclip_vision_patch14_384.safetensors | 0.86 GB |
wan_2.1_vae.safetensors | 0.25 GB |
Total: 13.74 GB
WindstormLabs/wan22-encoders.WindstormLabs/wan22-loras.Apache-2.0, inherited from the upstream Wan 2.2 release by Wan-AI (Alibaba). Licence text: LICENSE.
Mirror created 2026-05-13 from a local working copy. Hashes preserved via HF's content-addressed storage.