This repository contains Python code for various Natural Language Processing (NLP) tasks and Generative AI models, ranging from basic techniques to advanced applications.
- Basic NLP
- Text Classification
- Sentiment Analysis
- BERT
- Generative AI Models
- RAG (Retrieval-Augmented Generation)
- Fine-tuning with LoRA
- Tokenization
- Stemming and Lemmatization
- Part-of-Speech Tagging
- Named Entity Recognition
- Naive Bayes Classifier
- Support Vector Machines
- Deep Learning for Text Classification
- Rule-based Sentiment Analysis
- Machine Learning-based Sentiment Analysis
- VADER Sentiment Analysis
- BERT for Text Classification
- BERT for Question Answering
- BERT for Named Entity Recognition
- LLaMA-2 Implementation
- Google's Gemini Model Usage
- Implementing RAG with LLaMA-2
- RAG with Gemini
- Fine-tuning LLaMA-2 with LoRA
- LoRA for Domain Adaptation
- Python 3.8+
- PyTorch
- Transformers
- scikit-learn
- NLTK
- spaCy
For a complete list of dependencies, see requirements.txt
.
- Clone this repository: git clone https://github.com/vedica1011/NLP_BERT_TL.git
- Install the required packages: all are given in the notebook else you can create requirements.txt
Each directory contains Jupyter notebooks and Python scripts demonstrating various NLP and Generative AI techniques. Navigate to the specific directory and run the notebooks or scripts as needed.
Contributions are welcome! Please feel free to submit a Pull Request.
This project is licensed under the MIT License - see the LICENSE file for details.