Instructions to use FoundationVision/FlashVideo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use FoundationVision/FlashVideo with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("FoundationVision/FlashVideo", 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 library name, pipeline tag
#1
by nielsr HF Staff - opened
This PR adds a model card, which adds a link to the Github repo as well as a link to the project page.
It ensures the model can be found at https://huggingface.co/models?pipeline_tag=text-to-video and has the proper library tag.
shilongz changed pull request status to merged