File size: 1,454 Bytes
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author: cogvideox996
baseModel: CogVideoX
hashes:
AutoV1: 8A96607E
AutoV2: A410E48D98
AutoV3: 37ABB2444528
BLAKE3: F475F5AD96B6BB2A791A0DDD2C055810E4C12A4343CDD926BC2ED3B9ACE25FCD
CRC32: 1AB3FB12
SHA256: A410E48D988C8224CEF392B68DB0654485CFD41F345F4A3A81D3E6B765BB995E
metadata:
format: SafeTensor
modelPage: https://civitai.com/models/1009676?modelVersionId=1131953
preview:
- https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/39402559-7cc5-4e33-b8ff-895ad0769b60/width=450/43812071.jpeg
website: Civitai
---
# Trigger Words
No trigger words
# About this version
* **SHA256:** a410e48d988c8224cef392b68db0654485cfd41f345f4a3a81d3e6b765bb995e
* **Pointer size:** 134 Bytes
* **Size of remote file:** 862 MB
# CogVideoX-VAE
The model is released under a permissive CogVideoX license.
To get started with ComfyUI;
1. Update to the latest version of ComfyUI
2. Download CogVideoX model weights into `models/diffusion_models` folder, use "CogVideoXModelLoader" load
3. Make sure a text encoder [[1](https://civitai.com/models/497255?modelVersionId=568405)] is in your `models/clip` folder
4. Download the VAE to: `ComfyUI/models/vae, use "`CogVideoXVAELoader`" load`
CogVideoX has [kijai ComfyUI support](https://github.com/kijai/ComfyUI-CogVideoXWrapper), and will run on 20GB+ or 9GB VRAM.
Github: <https://github.com/THUDM/CogVideo>
HuggingFace: <https://huggingface.co/collections/THUDM/cogvideo-66c08e62f1685a3ade464cce>
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