| ## BAPULM: Binding Affinity Prediction Using Language Models | |
| Welcome to the BAPULM repository! This repository corresponds to the prediction of protein-ligand complex binding affinity. | |
| ## Getting Started | |
| 1. **Clone the Repository:** | |
| Run the following command in your terminal: | |
| ```bash | |
| git clone https://github.com/radh55sh/BAPULM.git | |
| cd BAPULM | |
| 2. **Install the required packages:** | |
| Using conda: | |
| ```bash | |
| conda create --name bapulm-env python=3.10 | |
| conda activate bapulm-env | |
| pip install -r requirements.txt | |
| 4. **Download the datset:** | |
| Download the prottrans_molformer dataset from the [Hugging Face Platform](https://huggingface.co/datasets/radh25sh/BAPULM/tree/main) and place it in the data/ directory. | |
| 5. **To train the model and inference:** | |
| First, train the model, and furthermore, to do inference on the model, download the model parameters from the [Hugging Face Platform](https://huggingface.co/datasets/radh25sh/BAPULM/tree/main) and place it in the data/ directory. | |
| ```bash | |
| python main.py # To train the model | |
| python inference.py # To perform inference | |