Image-to-Video
Diffusers
Safetensors
English
CogVideoXImageToVideoPipeline
cogvideox
video-generation
thudm
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
Improve model card with pipeline tag and library name
#17
by nielsr HF Staff - opened
README.md
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license: other
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license_link: https://huggingface.co/THUDM/CogVideoX-5b-I2V/blob/main/LICENSE
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inference: false
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license: other
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license_link: https://huggingface.co/THUDM/CogVideoX-5b-I2V/blob/main/LICENSE
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tags:
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- cogvideox
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- video-generation
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- thudm
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- image-to-video
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pipeline_tag: text-to-video
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library_name: diffusers
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inference: false
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