Instructions to use hf-internal-testing/tiny-cogvideox-pipe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hf-internal-testing/tiny-cogvideox-pipe with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hf-internal-testing/tiny-cogvideox-pipe", 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:
- 426a023243a766600e6a22c382e47c0d3f1c48ccd97cc8d074e781d58c5af1a8
- Size of remote file:
- 287 kB
- SHA256:
- f436e016388c72887baef17896544ed840757b6fb646b6058c9794c669c5169d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.