A one stop repository for generative AI research updates, interview resources, notebooks and much more!
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Updated
May 15, 2024
A one stop repository for generative AI research updates, interview resources, notebooks and much more!
This repository compiles code samples and notebooks demonstrating how to use Generative AI on Google Cloud Vertex AI.
Load local LLMs effortlessly in a Jupyter notebook for testing purposes alongside Langchain or other agents. Contains Oobagooga and KoboldAI versions of the langchain notebooks with examples.
Jupyter notebooks for enhancing your skills with ChatGPT based prompt engineering. Harness the potential of large language models and create innovative applications.
Concepts and examples on using and training LLMs
Jupyter notebooks for course Finetuning Large Language Models, taught by Sharon Zhou (Lamini) and Andrew Ng (DeepLearning.AI).
This project contains the lab notebooks from course: Large Language Models: Application through Production by Databricks
Notebooks showing off LangChain.js v0.1.0 features.
Advanced Retrieval-Augmented Generation (RAG) through practical notebooks, using the power of the Langchain, OpenAI GPTs ,META LLAMA3 , Agents.
Generative AI workshop delivered at PyDataBCN 2023
A comprehensive hub for updates on generative AI research, including interviews, notebooks, and additional resources.
Dive into Diverse Topics with Hands-on Python Notebooks
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
Notebooks for the Built Multi-Agent Applications with AutoGen Course
Run Dolly, the world’s first truly open instruction-tuned LLM, with your own prompts on IPUs
Herein lies my Jupyter Notebooks for the DeepLearning.AI ChatGPT Prompt Engineering for Developers course
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.
Colab notebooks exploring topics in Data Science and AI, discussed on the blog: https://medium.com/@jgrygolec
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