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Results

image info

Important remarks:

  • The quality of the model output might slightly vary compared to the base model. There might be minimal quality loss.
  • These results were obtained on NVIDIA A100-PCIE-40GB with configuration described in config.json and are obtained after a hardware warmup. Efficiency results may vary in other settings (e.g. other hardware, image size, batch size, ...).
  • You can request premium access to more compression methods and tech support for your specific use-cases here.

Setup

You can run the smashed model with these steps:

  1. Check cuda, torch, packaging requirements are installed. For cuda, check with nvcc --version and install with conda install nvidia/label/cuda-12.1.0::cuda. For packaging and torch, run pip install packaging torch.
  2. Install the pruna-engine available here on Pypi. It might take 15 minutes to install.
    pip install pruna-engine[gpu] --extra-index-url https://pypi.nvidia.com --extra-index-url https://pypi.ngc.nvidia.com --extra-index-url https://prunaai.pythonanywhere.com/
    
  3. Download the model files using one of these three options.
    • Option 1 - Use command line interface (CLI):
      mkdir stabilityai-stable-diffusion-xl-base-1.0-turbo-green-smashed
      huggingface-cli download PrunaAI/stabilityai-stable-diffusion-xl-base-1.0-turbo-green-smashed --local-dir stabilityai-stable-diffusion-xl-base-1.0-turbo-green-smashed --local-dir-use-symlinks False
      
    • Option 2 - Use Python:
      import subprocess
      repo_name = "stabilityai-stable-diffusion-xl-base-1.0-turbo-green-smashed"
      subprocess.run(["mkdir", repo_name])
      subprocess.run(["huggingface-cli", "download", 'PrunaAI/'+ repo_name, "--local-dir", repo_name, "--local-dir-use-symlinks", "False"])
      
    • Option 3 - Download them manually on the HuggingFace model page.
  4. Load & run the model.
    from pruna_engine.PrunaModel import PrunaModel
    
    model_path = "stabilityai-stable-diffusion-xl-base-1.0-turbo-green-smashed/model"  # Specify the downloaded model path.
    smashed_model = PrunaModel.load_model(model_path)  # Load the model.
    smashed_model(prompt='Beautiful fruits in trees', height=1024, width=1024)[0][0]  # Run the model where x is the expected input of.
    

Configurations

The configuration info are in config.json.

License

We follow the same license as the original model. Please check the license of the original model stabilityai/stable-diffusion-xl-base-1.0 before using this model.

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