This repository shares end-to-end notebooks on how to use various Weaviate features and integrations!

Interactive notes (Jupyter Notebooks) for building AI-powered applications

Perform RAG (Retrieval-Augmented Generation) from your PDFs using this Colab notebook! Powered by Llama 2

Jupyeter Notebooks that demo Generative AI concepts

Demo done in a jupyter notebook to show how Retrieval Augmented Generation (RAG) can be done without using any frameworks.

This repository includes a variety of notebooks designed for tasks ranging from generative ai text models to image generation and model training to data analysis and visualization.

This repository contains Jupyter notebooks to explore and utilize OpenAI's Large Language Models (LLMs) for various applications, including chatbots, retrieval-augmented generation, text generation, prompt engineering, and vector embedding. These notebooks provide a comprehensive toolkit for working with OpenAI models in diverse contexts.

This repository provides Jupyter notebooks to interact with Mistral Large Language Models (LLMs) for tasks including chatbot development, retrieval-augmented generation, and text generation. These notebooks are designed to help users leverage Mistral models in a range of applications, from conversational AI to content generation.

This repository provides Jupyter notebooks for exploring and utilizing Cohere's Large Language Models (LLMs) in various applications, including chatbots and retrieval-augmented generation (RAG). These notebooks serve as a practical guide for deploying Cohere models for conversational AI and information retrieval tasks.

This repository contains Jupyter notebooks for working with Anthropic Large Language Models (LLMs), providing tools to explore chat-based interactions, retrieval-augmented generation, and text generation. These notebooks serve as a practical introduction to leveraging Anthropic models for various applications.

Machine Learning, LLM and other Jupyter Notebooks and resources

Question-Answering with RAG and local LLMs over your Jupyter Notebooks

In this notebook combines LangChain and weaviate Database to ask questions related to your document. Powered by OpenAI's GPT-3.

Annotated Notebooks to dive into Self-Attention, In-Context Learning, RAG, Knowledge-Graphs, Fine-Tuning, Model Optimization, and many more.

Collection of Jupyter Notebooks related to Generative AI.

Notebooks supporting the activities for generative AI 102 Startup loft.

This repo contains google colab notebook for handing Docling for data extraction such as text, image, table etc.

This repo contains codes for RAG using docling on colab notebook with langchain, milvus, huggingface embedding model and LLM

An interactive insurance policy query-answering notebook with a Retrieval-Augmented Generation (RAG) pipeline with semantic search, caching, and GPT-based response generation.

This notebook showcases a prototype for a retrieval-augmented generation approach in question-answering. The implementation includes demonstrations using an offline language model (LLM) from Hugging Face and the OpenAI GPT-3.5 API.