Welcome to the official repository of the Multilingual Weighted Normalized Temperature Softmax (WNT-Softmax), developed by the Computational Intelligence and Biomedicine (ICB) group at the University of Málaga. This project leverages advanced machine learning techniques to enhance language processing tasks across multiple languages.
- Python 3.10+
- PyTorch 2.0.1
Clone the repository and install the required packages:
git clone https://github.com/FernandoGD97/WNT-Softmax.git
cd WNT-Softmaxpip install -r requirementsThe repository includes scripts for data generation and model training. Here are examples of how to use these scripts:
Generate data for Swedish using a machine translation model (If you don't have direct translation from spanish):
python data_generator.py --lang "sv" --model "Helsinki-NLP/opus-mt-en-sv" --data_path "../data/SympT-EMIST/en/train_df.tsv" --from_spanish false --log_file "../logs/data_generation_sv.log"Generate data for French:
python data_generator.py --lang "fr" --model "Helsinki-NLP/opus-mt-es-fr" --log_file "../logs/data_generation_fr.log"Train the model with English data for 10 epochs:
python WNT_Softmax_training.py --lang en --epochs 10 --log_file "../logs/wnt-multisapbert.log" --save_model True- Multilingual Support: Capable of processing and understanding multiple languages.
- Advanced Machine Learning Techniques: Utilizes state-of-the-art models and frameworks.
- High-Performance Computing: Initially deployed and tested on an NVIDIA RTX 2080 Ti GPU, though not a mandatory requirement.
We welcome contributions from the community. Please submit your pull requests to the main branch and ensure your code adheres to the existing style.