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Simple PyTorch Model Pipeline

This is a simple PyTorch model pipeline that can be used to train and evaluate a model. The pipeline is designed to be used with a simple feedforward neural network, but can be easily adapted to other models.

This is for experimental around model provenance and integrity.

A simple github action is used to run the pipeline.

Usage

Set up a virtualenv and install the requirements:

virtualenv -p python3 venv

source venv/bin/activate

pip install -r requirements.txt

Generate the training set:

python generate_dataset.py

Train the model:

python train_model.py

Inference:

python run_inference.py

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Example pipeline to explore model provenance

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