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
Time for CogVideo 2?
#19
by natalie5 - opened
I miss the time when I was experimenting with CogVideo.
I think it's time for CogVideo 2? Here are some papers that will help you reach SOTA performance for video models.
https://arxiv.org/abs/2508.15761
https://arxiv.org/abs/2506.09113
https://arxiv.org/abs/2506.10639
https://arxiv.org/abs/2505.07818