A lightweight tool to benchmark the performance of NLP models based on medical text datasets. It supports HuggingFace, ONNX, and ORT models and works with input data from CSV files or a PostgreSQL database.
- Compare multiple NLP models
- Supports HuggingFace, ONNX, and ORT model types
- Input from CSV or PostgreSQL database
- Outputs performance metrics like inference time and throughput
- Configurable via a single YAML file
git clone https://github.com/Holmusk/BenchMark.git
cd your-directory
create a virtual environment: python3 -m venv Enviornment
activate: source Enviornment/bin/activate
To install dependenices: pip install -r requirements.txt