A collection of hand on notebook for LLMs practitioner

Machine Learning, LLM and other Jupyter Notebooks and resources

LLM Jupyter Notebook Examples

LLM inference examples using the PyTorch Framework

An Open Source implementation of Notebook LM with more flexibility and features

Practical course about Large Language Models.

A collection of practical examples and tutorials for fine-tuning large language models using Factory. Includes Docker images, Jupyter notebooks, and utility scripts for easy model training and deployment.

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

This Jupyter notebook project evaluates the accuracy of language model responses to generated questions by comparing them to a ground truth dataset using cosine similarity and ROUGE metrics.

A complete pipeline for training, inference, and evaluation of a large language model (LLM) using Hugging Face. This repository includes notebooks, scripts, and configuration to take a model from raw data → fine-tuning/training → inference (with examples) plus evaluation and deployment readiness.

We treat a cognition-tuned LLM (Centaur) as an artificial participant to simulate cooperation in one-shot Prisoner’s Dilemmas. The notebook reproduces an orthogonal payoff design and reports context-specific (different social and economic scenarios) cooperation rates from transparent, fully reproducible runs.

LangChain & Prompt Engineering tutorials on Large Language Models (LLMs) such as ChatGPT with custom data. Jupyter notebooks on loading and indexing data, creating prompt templates, CSV agents, and using retrieval QA chains to query the custom data. Projects for using a private LLM for chat with PDF files, cryptocurrency tweets sentiment analysis.