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mlgawd
/
nsf4

Diffusers
Safetensors
8-bit precision
Model card Files Files and versions
xet
Community

Instructions to use mlgawd/nsf4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use mlgawd/nsf4 with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("mlgawd/nsf4", 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
nsf4
6.78 GB
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  • 1 contributor
History: 4 commits
mlgawd's picture
mlgawd
Upload pytorch3d-0.7.8-cp310-cp310-linux_x86_64.whl
f7fc574 verified over 1 year ago
  • .gitattributes
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    Upload pytorch3d-0.7.8-cp310-cp310-linux_x86_64.whl over 1 year ago
  • README.md
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  • config.json
    390 Bytes
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  • diffusion_pytorch_model.safetensors
    6.69 GB
    xet
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  • mmcv-2.2.0-cp310-cp310-linux_x86_64.whl
    34.2 MB
    xet
    Upload mmcv-2.2.0-cp310-cp310-linux_x86_64.whl over 1 year ago
  • pytorch3d-0.7.8-cp310-cp310-linux_x86_64.whl
    56.6 MB
    xet
    Upload pytorch3d-0.7.8-cp310-cp310-linux_x86_64.whl over 1 year ago