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Developer-friendly, serverless vector database for AI applications. Easily add long-term memory to your LLM apps!

Tensor search for humans.

Typed graph database where agents branch and merge like Git. S3-native, Rust, traversal + vector + BM25 in one runtime.

The transactional alternative to Elasticsearch, built on Postgres.

Scalable, fast, and disk-friendly vector search in Postgres, the successor of pgvecto.rs .

Vector database plugin for Postgres, written in Rust, specifically designed for LLM.

A Highly Scalable Distributed Vector Search Engine

A distributed system for embedding-based vector retrieval

A Python vector database you just need - no more, no less.

Weaviate is an open source vector search engine that stores both objects and vectors, allowing for combining vector search with structured filtering with the fault-tolerance and scalability of a cloud-native database, all accessible through GraphQL, REST, and various language clients.

Deterministic Python orchestrator for 37 CLI coding agents (Claude Code, Codex CLI, Gemini CLI, GitHub Copilot CLI, Cursor, Aider, OpenHands, OpenCode, Goose, Qwen, Ollama, ...) running in parallel git worktrees. First-class MCP server, quality gates, cost tracking with budgets.

CodeGeeX: An Open Multilingual Code Generation Model (KDD 2023)

CodeGen is an open-source model for program synthesis. Trained on TPU-v4. Competitive with OpenAI Codex.

Open Code LLMs for Code Understanding and Generation.

An open-source alternative to GitHub Copilot server

Smart code context extractor for AI assistants with accurate token counting and budget management

Run VS Code on any machine anywhere and access it in the browser.

OS-agnostic, system-level binary package manager and ecosystem.

Moby is an open-source project created by Docker to enable and accelerate software containerization.

🏕️ Reproducible development environment for AI/ML.

The Jupyter notebook is a web-based notebook environment for interactive computing.

A build, packaging, and run system for ephemeral multi-container environments.

Instruct-tune LLaMA on consumer hardware

A PyTorch Lightning extension that accelerates and enhances foundation model experimentation with flexible fine-tuning schedules.

An Extensible Toolkit for Finetuning and Inference of Large Foundation Models

Using Low-rank adaptation to quickly fine-tune diffusion models.

An optimized prompt tuning strategy achieving comparable performance to fine-tuning on small/medium-sized models and sequence tagging challenges. (ACL 2022)

Efficient finetuning approach that reduces memory usage enough to finetune a 65B parameter model on a single 48GB GPU while preserving full 16-bit finetuning task performance.

Train transformer language models with reinforcement learning.

🚀 A simple way to train and use PyTorch models with multi-GPU, TPU, mixed-precision.

Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler.

A tool designed to streamline the fine-tuning of various AI models, offering support for multiple configurations and architectures.

Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

Kedro is an open-source Python framework for creating reproducible, maintainable and modular data science code.

MegEngine is a fast, scalable and easy-to-use deep learning framework, with auto-differentiation.

Metric Learning Algorithms in Python.