nlp-tasks

The repository contains a series of natural language processing (NLP) tasks tackled using Transformers models and standard open-source datasets.
Its implementation primarily utilizes PyTorch, heavily relying on the HuggingFace Transformers and PEFT libraries.
The intention is to have a codebase for experimenting with different models on various standard datasets, therefore the repository has more of a demonstrative or experimental purpose.
Tasks included are:

• [✅] Text Classification
• [✅] Named Entity Recognition
• [✅] Question Answering
• [✅] Summarization
• [✅] Causal Llm
• [] Instruction Fine tuning Llm

How to Run

1. Initial setup
   1.1 Create a new conda environment to install the dependencies, and activate it:

   conda create -n nlp-tasks-env python=3.11 -y
   conda activate nlp-tasks-env

   1.2 Install the dependencies:

   pip install git+https://github.com/sarapiscitelli/nlp-tasks/

   1.3 Clone the repository to get the scripts:

   git clone https://github.com/sarapiscitelli/nlp-tasks.git

2. Run the experiments
   Training:

   python scripts/train/<task name>.py

   Evaluation:

   python scripts/evaluate/<task name>.py --model_name_or_checkpoin_path <path_to_model>