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seedleap
/
zing-0.5

Image-to-Video
Diffusers
Safetensors
world-model
video-generation
text-to-video
action-conditioned
causal
Model card Files Files and versions
xet
Community
2

Instructions to use seedleap/zing-0.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use seedleap/zing-0.5 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("seedleap/zing-0.5", 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
zing-0.5 / pretrained
14.2 GB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 1 commit
Seedleap.ai
init
d7b5bb1 8 days ago
  • text_encoder
    init 8 days ago
  • tokenizer
    init 8 days ago
  • vae
    init 8 days ago