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models/vae/cog/cogvideox_vae_fp32.md
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---
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author: cogvideox996
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baseModel: CogVideoX
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hashes:
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AutoV1: 8A96607E
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AutoV2: A410E48D98
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AutoV3: 37ABB2444528
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BLAKE3: F475F5AD96B6BB2A791A0DDD2C055810E4C12A4343CDD926BC2ED3B9ACE25FCD
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CRC32: 1AB3FB12
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SHA256: A410E48D988C8224CEF392B68DB0654485CFD41F345F4A3A81D3E6B765BB995E
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metadata:
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format: SafeTensor
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modelPage: https://civitai.com/models/1009676?modelVersionId=1131953
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preview:
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- https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/39402559-7cc5-4e33-b8ff-895ad0769b60/width=450/43812071.jpeg
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website: Civitai
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---
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# Trigger Words
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No trigger words
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# About this version
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* **SHA256:** a410e48d988c8224cef392b68db0654485cfd41f345f4a3a81d3e6b765bb995e
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* **Pointer size:** 134 Bytes
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* **Size of remote file:** 862 MB
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# CogVideoX-VAE
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The model is released under a permissive CogVideoX license.
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To get started with ComfyUI;
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1. Update to the latest version of ComfyUI
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2. Download CogVideoX model weights into `models/diffusion_models` folder, use "CogVideoXModelLoader" load
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3. Make sure a text encoder [[1](https://civitai.com/models/497255?modelVersionId=568405)] is in your `models/clip` folder
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4. Download the VAE to: `ComfyUI/models/vae, use "`CogVideoXVAELoader`" load`
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CogVideoX has [kijai ComfyUI support](https://github.com/kijai/ComfyUI-CogVideoXWrapper), and will run on 20GB+ or 9GB VRAM.
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Github: <https://github.com/THUDM/CogVideo>
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HuggingFace: <https://huggingface.co/collections/THUDM/cogvideo-66c08e62f1685a3ade464cce>
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