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Stars
A curated list of awesome responsible machine learning resources.
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
🌐 Make websites accessible for AI agents. Automate tasks online with ease.
Robust representation of semantically constrained graphs, in particular for molecules in chemistry
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
Documentation that simply works
Fréchet ChemNet Distance: A quality measure for generative models for molecules
Kickstart your LLMOps initiative with a flexible, robust, and productive Python package.
Open Source Machine Learning Research Platform designed for frontier AI/ML workflows. Local, on-prem, or in the cloud. Open source.
GenAI Agent Framework, the Pydantic way
🐫 CAMEL: The first and the best multi-agent framework. Finding the Scaling Law of Agents. https://www.camel-ai.org
This is a curated list for Information Bottleneck Principle, in memory of Professor Naftali Tishby.
PyMuPDF is a high performance Python library for data extraction, analysis, conversion & manipulation of PDF (and other) documents.
A collection of inspiring lists, manuals, cheatsheets, blogs, hacks, one-liners, cli/web tools and more.
Fine-tuning & Reinforcement Learning for LLMs. 🦥 Train OpenAI gpt-oss, DeepSeek-R1, Qwen3, Gemma 3, TTS 2x faster with 70% less VRAM.
The Security Toolkit for LLM Interactions
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
the scott CPU from "But How Do It Know?" by J. Clark Scott
A curated collection of adversarial attack and defense on graph data.
🦔 PostHog is an all-in-one developer platform for building successful products. We offer product analytics, web analytics, session replay, error tracking, feature flags, experimentation, surveys, d…
ADRepository: Real-world anomaly detection datasets, including tabular data (categorical and numerical data), time series data, graph data, image data, and video data.
Plug in and Play Implementation of Tree of Thoughts: Deliberate Problem Solving with Large Language Models that Elevates Model Reasoning by atleast 70%