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Generative AI projects including concepts such as RAG, Fine-tuning, Conversation Retrieval, etc.

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Learning Generative AI Repository

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:

  1. Clone the repository using git clone https://github.com/sharmapratik88/LearningAI.git.
  2. Navigate to the folder of interest.
  3. Review each folder's README.md files for detailed instructions on accessing the materials or running the projects.

Contributing

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.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contact

For questions or to connect, please reach out to me:

Thank you for visiting my Learning Generative AI repository!