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lightx2v
/
Minimax-h3-Turbo

Image-to-Video
Diffusers
English
Chinese
t2v
i2v
r2v
Model card Files Files and versions
xet
Community
8

Instructions to use lightx2v/Minimax-h3-Turbo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use lightx2v/Minimax-h3-Turbo with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    from diffusers.utils import load_image, export_to_video
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("lightx2v/Minimax-h3-Turbo", dtype=torch.bfloat16, device_map="cuda")
    pipe.to("cuda")
    
    prompt = "A man with short gray hair plays a red electric guitar."
    image = load_image(
        "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png"
    )
    
    output = pipe(image=image, prompt=prompt).frames[0]
    export_to_video(output, "output.mp4")
  • Notebooks
  • Google Colab
  • Kaggle
Minimax-h3-Turbo
1.38 GB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 4 commits
lightx2v's picture
lightx2v
X-niper's picture
X-niper
Update README.md (#5)
b65e359 about 11 hours ago
  • .gitattributes
    1.52 kB
    initial commit about 13 hours ago
  • README.md
    255 Bytes
    Update README.md (#5) about 11 hours ago
  • minimax_h3_fl2v_turbo_4step_v0.1.safetensors
    1.38 GB
    xet
    Upload minimax_h3_fl2v_turbo_4step_v0.1.safetensors with huggingface_hub about 13 hours ago