Welcome to the Learning Generative AI GitHub repository! This repository documents my journey through the fascinating world of generative AI, including code, resources, and learnings.
| Sr No | Notebook | Description |
|---|---|---|
| 1 | PDF Q&A Retrieval with AWQ Quantization, Mistral Instruct v0.2, and vLLM | Project demonstrates a comprehensive process for handling PDF documents, embedding their content into a Chroma vector database, and utilizing a quantized language model for retrieval-based question answering. The steps involved include loading and processing PDF documents, embedding text into a vector database, quantizing a language model using AWQ quantization technique, and setting up a retrieval-based QA system using Langchain and vLLM. |
| 2 | PDF Q&A Retrieval with LangChain & GROQ API | Project is designed to create a QA system using a PDF document as the knowledge base leveraging the GROQ API LLM. |
| 3 | Hybrid Search Using Ensemble and Weaviate Hybrid Retrievers | The project implements a hybrid search system that combines multiple retrieval techniques a) Ensemble Retriever: Uses BM25 for keyword-based retrieval. Employs dense retrieval with Sentence Transformer for semantic-based retrieval. b) Weaviate Hybrid Retriever: Another vector database used alongside the Ensemble Retriever. Supports Hybrid search. |
| 4 | Machine Translation Using Transformers | A demonstration of machine translation using Hugging Face's Transformers library. |
| 5 | Text Summarization Using Transformers | This project showcases text summarization capabilities using Hugging Face's Transformers. |
| 6 | Text Classification Using Transformers | A project demonstrating how to perform text classification using Hugging Face's Transformers library. |
| 7 | ChatGPT Prompt Engineering for Developers | Course learnings from DeepLearning.AI's ChatGPT Prompt Engineering for Developers. It covers summarizing, inferring, transforming, and expanding text to build custom chatbots and other applications. I wrote the blog on this: Decoding ChatGPT: The Ultimate Guide to LLM Mastery. Course Link for reference. |
| 8 | Building Systems with ChatGPT | Course Learnings from DeepLearning.AI's Building Systems with ChatGPT. Taught by Isa Fulford and Andrew Ng, this course teaches how to build multi-step systems efficiently using large language models. It includes learning to split complex tasks into a pipeline of subtasks and evaluating LLM inputs and outputs for safety, accuracy, and relevance. Course Link for reference. |
To explore this repository:
- Clone the repository using
git clone https://github.com/sharmapratik88/LearningAI.git. - Navigate to the folder of interest.
- Review each folder's
README.mdfiles for detailed instructions on accessing the materials or running the projects.
This repository serves as a personal portfolio of my learning journey. However, I welcome suggestions, improvements, and contributions from the community. Feel free to open an issue or submit a pull request if you have any.
This project is licensed under the MIT License - see the LICENSE file for details.
For questions or to connect, please reach out to me:
- LinkedIn: Pratik Sharma
Thank you for visiting my Learning Generative AI repository!