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yitongl
/
sparse_quant_exp

Diffusers
Safetensors
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Diffusers

    How to use yitongl/sparse_quant_exp with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("yitongl/sparse_quant_exp", 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
sparse_quant_exp / backend_snapshot /fastvideo
343 kB
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  • 1 contributor
History: 2 commits

This model has 1 file scanned as unsafe.

yitongl's picture
yitongl
Add inference code and attention settings for sfp4 checkpoint-750
697fddf verified 16 days ago
  • api
    Add inference code and attention settings for sfp4 checkpoint-750 16 days ago
  • attention
    Upload backend snapshot for sfp4 checkpoint-750 16 days ago
  • configs
    Add inference code and attention settings for sfp4 checkpoint-750 16 days ago
  • entrypoints
    Add inference code and attention settings for sfp4 checkpoint-750 16 days ago
  • pipelines
    Add inference code and attention settings for sfp4 checkpoint-750 16 days ago
  • platforms
    Upload backend snapshot for sfp4 checkpoint-750 16 days ago
  • train
    Upload backend snapshot for sfp4 checkpoint-750 16 days ago
  • training
    Upload backend snapshot for sfp4 checkpoint-750 16 days ago
  • fastvideo_args.py
    52.1 kB
    Add inference code and attention settings for sfp4 checkpoint-750 16 days ago
  • forward_context.py
    4.03 kB
    Upload backend snapshot for sfp4 checkpoint-750 16 days ago