Dive into Diverse Topics with Hands-on Python Notebooks

Notebooks for the Built Multi-Agent Applications with AutoGen Course

Herein lies my Jupyter Notebooks for the DeepLearning.AI ChatGPT Prompt Engineering for Developers course

Colab notebook using llama 2 chat model answering questions as a deep learning expert by focusing on specific books and papers

This project contains the notebooks of the Deep Learning AI course "Langchain: Chat with your Data" running an a docker image with all dependencies.

This repository contains a collection of script files and notebooks documenting our deep learning progress and revisions. We regularly update and push new content as we explore various concepts and deepen our understanding.

QA With Jupyter NoteBook(.ipynb) powered by LangChain & Anthropic

Machine Learning, LLM and other Jupyter Notebooks and resources

A Concise Notebook to Summarize Your iMessage Conversations

Colab notebooks exploring topics in Data Science and AI, discussed on the blog: https://medium.com/@jgrygolec

Generative AI workshop delivered at PyDataBCN 2023

A data analasys application in a Jupyter Notebook that is able to determine the efficiency of the GPT API and BERT in classifying scientific papers.

Repository for running LLMs efficiently on Mac silicon (M1, M2, M3). Features Jupyter notebook for Meta-Llama-3 setup using MLX framework, with install guide & perf tips. Aims to optimize LLM performance on Mac silicon for devs & researchers.

Notebook for Flan-T5 – an alternative to large language models like GPT-3 & GPT-4 for NLP tasks like named entity recognition and text generation.

This project contains the lab notebooks from course: Large Language Models: Application through Production by Databricks

Pre-Training and Fine-Tuning transformer models using PyTorch and the Hugging Face Transformers library. Whether you're delving into pre-training with custom datasets or fine-tuning for specific classification tasks, these notebooks offer explanations and code for implementation.

Advanced Retrieval-Augmented Generation (RAG) through practical notebooks, using the power of the Langchain, OpenAI GPTs ,META LLAMA3 , Agents.

A comprehensive hub for updates on generative AI research, including interviews, notebooks, and additional resources.

Run Dolly, the world’s first truly open instruction-tuned LLM, with your own prompts on IPUs

Jupyter notebooks for course Finetuning Large Language Models, taught by Sharon Zhou (Lamini) and Andrew Ng (DeepLearning.AI).