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!

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Results

Important remarks:

The quality of the model output might slightly vary compared to the base model.
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, ...).
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Results mentioning "first" are obtained after the first run of the model. The first run might take more memory or be slower than the subsequent runs due cuda overheads.

Setup

You can run the smashed model with these steps:

Check that you have linux, python 3.10, and cuda 12.1.0 requirements installed. For cuda, check with nvcc --version and install with conda install nvidia/label/cuda-12.1.0::cuda.

Install the pruna-engine available here on Pypi. It might take up to 15 minutes to install.

pip install pruna-engine[gpu]==0.6.0 --extra-index-url https://pypi.nvidia.com --extra-index-url https://pypi.ngc.nvidia.com --extra-index-url https://prunaai.pythonanywhere.com/

Download the model files using one of these three options.

Option 1 - Use command line interface (CLI):

mkdir segmind-SSD-1B-turbo-tiny-green-smashed
huggingface-cli download PrunaAI/segmind-SSD-1B-turbo-tiny-green-smashed --local-dir segmind-SSD-1B-turbo-tiny-green-smashed --local-dir-use-symlinks False

Option 2 - Use Python:

import subprocess
repo_name = "segmind-SSD-1B-turbo-tiny-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.

Load & run the model.

from pruna_engine.PrunaModel import PrunaModel

model_path = "segmind-SSD-1B-turbo-tiny-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.

Credits & License

We follow the same license as the original model. Please check the license of the original model segmind/SSD-1B before using this model which provided the base model.

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