This project focuses on building and experimenting with Large Language Models (LLMs) for natural language understanding and generation tasks. It includes training, fine-tuning, and deploying models to handle tasks such as text generation, question answering, summarization, and conversational AI.
- Data preprocessing and cleaning
- Implementation of transformer-based LLMs
- Fine-tuning and model optimization
- Text generation, summarization, and QA
- Evaluation using NLP metrics
- Deployment-ready model pipelines
- Python 3.10+
- Libraries:
Hugging Face Transformers– LLM modelsPyTorch/TensorFlow– Deep learning frameworksdatasets– NLP datasetsnumpy/pandas– Data manipulationscikit-learn– Model evaluation metrics- Jupyter Notebook