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
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Download README.md from FoundationVision/FlashVideo: direct link, hf CLI and curl.
- Browser
- Download file 351 Bytes
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https://huggingface.co/FoundationVision/FlashVideo/resolve/main/README.md
- Command line
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hf download hf://FoundationVision/FlashVideo/README.md
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curl -L -o README.md https://huggingface.co/FoundationVision/FlashVideo/resolve/main/README.md
351 Bytes
metadata
license: mit
library_name: diffusers
pipeline_tag: text-to-video
FlashVideo
This repository contains the weights for the model described in the paper FlashVideo: Flowing Fidelity to Detail for Efficient High-Resolution Video Generation.
Project page: https://jshilong.github.io/flashvideo-page/