Basic Video Generation Tutorial
The VideoGenerator class provides the primary Python interface for doing offline video generation, which is interacting with a diffusion pipeline without using a separate inference api server.
Requirements
- At least a single NVIDIA GPU with CUDA 12.4.
- Python 3.10-3.12
Installation
If you have not installed FastVideo, please following these instructions first.
Usage
The first script in this example shows the most basic usage of FastVideo. If you are new to Python and FastVideo, you should start here.
# if you have not cloned the directory:
git clone https://github.com/hao-ai-lab/FastVideo.git && cd FastVideo
python examples/inference/basic/basic.py
For an example on Apple silicon:
python examples/inference/basic/basic_mps.py
For an example running DMD+VSA inference:
python examples/inference/basic/basic_dmd.py
For the typed config/request path added during the inference API refactor:
python examples/inference/basic/basic_dmd_new_api.py
For the few-step (4-step, DMD2-distilled) MiniMax-H3 preview, generating synchronized video and audio, optionally with block-sparse VSA attention:
python examples/inference/basic/basic_fasth3.py --prompt "your prompt" [--vsa-sparsity 0.9]
The default checkpoint FastVideo/FastVideo-Minimax-FastH3-Preview-v0.1 is private on the Hub while its license review completes; until it flips public, pass --model-path with a local snapshot of the release.
On Blackwell (sm_100) GPUs with a fastvideo-kernel build that carries the sm_100a block-sparse extension, --vsa-kernel sm100a routes the tile-64 attention forwards through the CUDA kernel instead of Triton (it sets FASTVIDEO_VSA_SM100A=1 before the pipeline boots); if the extension or the arch is missing, the run warns once and falls back to Triton.
Basic Walkthrough
All you need to generate videos using multi-gpus from state-of-the-art diffusion pipelines is the following few lines!
from fastvideo import VideoGenerator
def main():
generator = VideoGenerator.from_pretrained(
"Wan-AI/Wan2.1-T2V-1.3B-Diffusers",
num_gpus=1,
)
prompt = ("A curious raccoon peers through a vibrant field of yellow sunflowers, its eyes "
"wide with interest. The playful yet serene atmosphere is complemented by soft "
"natural light filtering through the petals. Mid-shot, warm and cheerful tones.")
video = generator.generate_video(prompt)
if __name__ == "__main__":
main()