Instructions to use zai-org/CogVideoX-5b-I2V with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use zai-org/CogVideoX-5b-I2V with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("zai-org/CogVideoX-5b-I2V", dtype=torch.bfloat16, device_map="cuda") pipe.to("cuda") prompt = "A man with short gray hair plays a red electric guitar." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png" ) output = pipe(image=image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
Upload VAE in fp32 (#13)
Browse files- Upload VAE in fp32 (567fb6a18b1ae8dbb9fcf29c3ea1f17de05bd9ed)
- Update vae/config.json (f03dce9522087167fb0c9a431976e46871f2df80)
Co-authored-by: Aryan V S <a-r-r-o-w@users.noreply.huggingface.co>
vae/config.json
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{
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"_class_name": "AutoencoderKLCogVideoX",
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"_diffusers_version": "0.
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"act_fn": "silu",
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"block_out_channels": [
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128,
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"CogVideoXUpBlock3D"
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],
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"use_post_quant_conv": false,
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"use_quant_conv": false
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}
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{
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"_class_name": "AutoencoderKLCogVideoX",
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"_diffusers_version": "0.32.0.dev0",
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"act_fn": "silu",
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"block_out_channels": [
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128,
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"CogVideoXUpBlock3D"
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],
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"use_post_quant_conv": false,
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"use_quant_conv": false,
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"invert_scale_latents": false
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}
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vae/diffusion_pytorch_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:a410e48d988c8224cef392b68db0654485cfd41f345f4a3a81d3e6b765bb995e
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size 862388596
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