Instructions to use kp-forks/CogVideoX-Fun-2b-InP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kp-forks/CogVideoX-Fun-2b-InP with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kp-forks/CogVideoX-Fun-2b-InP", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5a43aca976b28c542ee4fb7f7669baf40dd4c0332c0041903cd1e05e45a36b96
- Size of remote file:
- 431 MB
- SHA256:
- e25e94a8fc70774349bb4a03b8ef272f5d80f934863f7b0552c37c6a74f91542
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