sharpenb's picture
Upload folder using huggingface_hub (#2)
388ad10 verified
|
raw
history blame
4.47 kB
metadata
license: apache-2.0
library_name: pruna-engine
thumbnail: >-
  https://assets-global.website-files.com/646b351987a8d8ce158d1940/64ec9e96b4334c0e1ac41504_Logo%20with%20white%20text.svg
metrics:
  - memory_disk
  - memory_inference
  - inference_latency
  - inference_throughput
  - inference_CO2_emissions
  - inference_energy_consumption

Simply make AI models cheaper, smaller, faster, and greener!

Twitter GitHub LinkedIn

  • Give a thumbs up if you like this model!
  • Contact us and tell us which model to compress next here.
  • Request access to easily compress your own AI models here.
  • Read the documentations to know more here
  • Share feedback and suggestions on the Slack of Pruna AI (Coming soon!).

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 Linaqruf-animagine-xl-turbo-green-smashed
      huggingface-cli download PrunaAI/Linaqruf-animagine-xl-turbo-green-smashed --local-dir Linaqruf-animagine-xl-turbo-green-smashed --local-dir-use-symlinks False
      
    • Option 2 - Use Python:
      import subprocess
      repo_name = "Linaqruf-animagine-xl-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 = "Linaqruf-animagine-xl-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 Linaqruf/animagine-xl before using this model.

Want to compress other models?

  • Contact us and tell us which model to compress next here.
  • Request access to easily compress your own AI models here.