Instructions to use stepfun-ai/stepvideo-t2v with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stepfun-ai/stepvideo-t2v with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stepfun-ai/stepvideo-t2v", 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
Add metadata and Github repository link
#1
by nielsr HF Staff - opened
This PR adds the pipeline tag, ensuring the model can be found at https://huggingface.co/models?pipeline_tag=text-to-video.
It also adds the library name and the Github repository link to the model card.
fisherma changed pull request status to merged