A one stop repository for generative AI research updates, interview resources, notebooks and much more!

A curated collection of AI agent research papers released in 2026, covering agent engineering, memory, evaluation, workflows, and autonomous systems.

📖 A curated list of LegalNLP resources from all around the web.

A fork of Anthropic Computer Use that you can run on Mac computers to give Claude and other AI models autonomous access to your computer.

🐻 Bear necessities for state management in React

Instruct-tune LLaMA on consumer hardware

Full named-entity (i.e., not tag/token) evaluation metrics based on SemEval’13

Get up and running with Kimi-K2.6, GLM-5.2, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models.

A framework for few-shot evaluation of language models.

A Python and R autograding solution

The repository contains the code and dataset for the Socratic Debugging task which is a novel task for Socratically Questioning Novice Debuggers to guide them towards discovering and fixing a buggy…

Must-read papers on prompt-based tuning for pre-trained language models.

Solve puzzles. Learn CUDA.

Flexible Python configuration system. The last one you will ever need.

MiniLLM is a minimal system for running modern LLMs on consumer-grade GPUs

GPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use.

🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.

Inference code for Llama models

Running large language models on a single GPU for throughput-oriented scenarios.

A Python Data Valuation Package

Commonly used machine learning vocabulary in both English and Simplified Chinese

Implementation for https://arxiv.org/abs/2005.00652

This repo contains datasets and code for On the Interplay Between Fine-tuning and Composition in Transformers, by Lang Yu and Allyson Ettinger.

Knowledge extraction from semi-structured web.

♞ lichess.org: the forever free, adless and open source chess server ♞

starter from "How to Train a GAN?" at NIPS2016

Connectionist Temporal Classification (CTC) decoding algorithms: best path, beam search, lexicon search, prefix search, and token passing. Implemented in Python.

PyTorch implementations of Generative Adversarial Networks.

A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API