Welcome to the LLM Projects Archive! This repository serves as a curated collection of projects related to Large Language Models (LLMs). If you are interested in exploring and contributing to projects that leverage LLMs for various applications, you're in the right place.

• Introduction
• How to Contribute
• Projects
• License

Large Language Models (LLMs), such as GPT-3, BERT, and others, have revolutionized natural language processing and understanding. This repository aims to bring together a diverse set of projects that utilize LLMs for different purposes. Whether it's text generation, sentiment analysis, summarization, or any other application, this archive aims to showcase the versatility and creativity of LLM-based projects.

We encourage you to contribute to this archive by adding your own LLM-related projects or discovering new ones. Follow these steps to contribute:

1. Fork the repository.
2. Add your project information to the projects.md file. Include the project name, a brief description, and the GitHub repository link.
3. If your project falls into a specific category (e.g., sentiment analysis, chatbots, translation), please categorize it accordingly.
4. Submit a pull request.

Please adhere to the contributing guidelines for a smooth collaboration.

1. Introduction to LLMs:

   • Description: A comprehensive GitHub project offering a beginner-friendly guide and hands-on examples to understand and work with Large Language Models (LLMs) in the field of NLP( Natural Language Processing).
   • Repository: Introduction to LLMs

2. Customize Word Embeddings for LLMs:

   • Description: It's a GitHub project focused on tailoring word embeddings specifically for Large Language Models, enabling fine-tuned linguistic representations to enhance performance in domain-specific applications
   • Repository: Customize Word Embeddings for LLMs

3. Finetune Open-source LLMs on Custom Data:

   • Description: It's a GitHub project focused on fine-tuning open-source LLMs on custom datasets, showcasing tailored solutions for enhanced language models.
   • Repository: Finetune Open-source LLMs on custom data

4. Build & evaluate Retrieval-Augmented-Generation pipelines:

   • Description: A comprehensive GitHub project focused on building and evaluating Retrieval-Augmented-Generation pipelines, enhancing natural language understanding and generation capabilities."
   • Repository: Build & evaluate Retrieval-Augmented-Generation pipelines

5. Finetune Llama using QLoRA Method:

   • Description: "GitHub project for fine-tuning the Llama language model using the QLoRA (Quantized Low Rank Adaption) method for enhanced natural language understanding."
   • Repository: Finetune Llama using QLoRA Method

6. Conversationl AI system using LLMs on E-commerce Data:

   • Description: An innovative Conversational AI system leveraging Large Language Models (LLMs) for enhanced customer interaction and support, specifically tailored for E-commerce Data.
   • Repository: Conversationl AI system using LLMs on E-commerce Data

7. Build RAG-pipelines using Llama-Index:

   • Description: Build a RAG pipeline using Llama-Index.
   • Repository: Build RAG-pipelines using Llama-Index

This repository and its contents are open-sourced under the MIT License. Feel free to use, modify, and distribute these projects in accordance with the terms specified in the license.

If you encounter any issues or have suggestions for improvement, please open an issue in the Issues section of this repository.

The code has been tested on Windows system. It should work well on other distributions but has not yet been tested. In case of any issue with installation or otherwise, please contact me on Linkedin

Happy coding!!

I’m a seasoned Data Scientist and founder of TowardsMachineLearning.Org. I've worked on various Machine Learning, NLP, and cutting-edge deep learning frameworks to solve numerous business problems.