Source fastvideo/v1/examples/inference/basic.

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.

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.

python fastvideo/v1/examples/inference/basic/basic.py

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

generator = VideoGenerator.from_pretrained(
    "FastVideo/FastHunyuan-Diffusers",
    num_gpus=2,
)

prompt = "A beautiful woman in a red dress walking down a street"
video = generator.generate_video(prompt)

More to come! These examples and APIs are still under construction!

Example materials

basic.py

from fastvideo import VideoGenerator
# from fastvideo.v1.configs.sample import SamplingParam

def main():
    # FastVideo will automatically use the optimal default arguments for the
    # model. 
    # If a local path is provided, FastVideo will make a best effort
    # attempt to identify the optimal arguments.
    generator = VideoGenerator.from_pretrained(
        "FastVideo/FastHunyuan-diffusers",
        # if num_gpus > 1, FastVideo will automatically handle distributed setup
        num_gpus=4,
    )

    # sampling_param = SamplingParam.from_pretrained("/workspace/data/Wan-AI/Wan2.1-I2V-14B-480P-Diffusers")
    # sampling_param.num_frames = 45
    # sampling_param.image_path = "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/astronaut.jpg"
    # Generate videos with the same simple API, regardless of GPU count
    prompt = "A beautiful woman in a red dress walking down a street"
    video = generator.generate_video(prompt)
    # video = generator.generate_video(prompt, sampling_param=sampling_param, output_path="wan_t2v_videos/")

    # Generate another video with a different prompt, without reloading the
    # model!
    prompt2 = "A beautiful woman in a blue dress walking down a street"
    video2 = generator.generate_video(prompt2)


if __name__ == "__main__":
    main()