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Stars
Generative AI reference workflows optimized for accelerated infrastructure and microservice architecture.
Building Large Language Model Applications, Published by Packt
Algorithms for explaining machine learning models
TextAttack 🐙 is a Python framework for adversarial attacks, data augmentation, and model training in NLP https://textattack.readthedocs.io/en/master/
18 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/
A modular graph-based Retrieval-Augmented Generation (RAG) system
dennisbakhuis / pigeonXT
Forked from agermanidis/pigeon🐦 Quickly annotate data from the comfort of your Jupyter notebook
This repository contains demos I made with the Transformers library by HuggingFace.
DSPy: The framework for programming—not prompting—foundation models
Machine Learning Engineering Open Book
Guide for fine-tuning Llama/Mistral/CodeLlama models and more
llama3 implementation one matrix multiplication at a time
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
Dropbox LLM Security research code and results
The simplest, fastest repository for training/finetuning medium-sized GPTs.
Minimal and clean examples of machine learning algorithms implementations
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
Implementing a ChatGPT-like LLM in PyTorch from scratch, step by step
Master programming by recreating your favorite technologies from scratch.
The Security Toolkit for LLM Interactions