Stars
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
All Algorithms implemented in Python
Get up and running with OpenAI gpt-oss, DeepSeek-R1, Gemma 3 and other models.
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
Langflow is a powerful tool for building and deploying AI-powered agents and workflows.
21 Lessons, Get Started Building with Generative AI
Robust Speech Recognition via Large-Scale Weak Supervision
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
GPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use.
List of Computer Science courses with video lectures.
Examples and guides for using the OpenAI API
A curated list of awesome C++ (or C) frameworks, libraries, resources, and shiny things. Inspired by awesome-... stuff.
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga…
A high-throughput and memory-efficient inference and serving engine for LLMs
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
CLI platform to experiment with codegen. Precursor to: https://lovable.dev
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
The simplest, fastest repository for training/finetuning medium-sized GPTs.
Making large AI models cheaper, faster and more accessible
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.
Google Research
Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
Code and documentation to train Stanford's Alpaca models, and generate the data.