Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing
    • Website
      • Tasks
      • HuggingChat
      • Collections
      • Languages
      • Organizations
    • Community
      • Blog
      • Posts
      • Daily Papers
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

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 /training
53.3 kB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
yitongl's picture
yitongl
Upload backend snapshot for sfp4 checkpoint-750
4db877c verified 26 days ago
  • training_pipeline.py
    50.8 kB
    Upload backend snapshot for sfp4 checkpoint-750 26 days ago
  • wan_training_pipeline.py
    2.49 kB
    Upload backend snapshot for sfp4 checkpoint-750 26 days ago