Burn is a next generation tensor library and Deep Learning Framework that doesn't compromise on flexibility, efficiency and portability.
⚙️ 深度学习基础库
PyTorch、Transformers、JAX 等底层框架与工具
全部 1028🧠 大语言模型 24🤖 AI 智能体 160🧩 应用开发平台 23📚 RAG 与知识库 47💬 聊天界面与客户端 43🖥️ 本地推理与部署 86👨💻 AI 编程 94🛠️ 开发框架与 SDK 46🔌 MCP 与工具生态 35🎨 图像生成 24🎬 视频生成 17🎙️ 语音与音频 44👁️ 计算机视觉 27📄 文档解析与抓取 23🗄️ 向量数据库 25🏋️ 训练微调与 MLOps 73🧪 评测·观测·安全 75🚪 API 网关与代理 12🔎 搜索与深度研究 15⚙️ 深度学习基础库 55🏷️ 数据与标注 31🔬 行业与科研 AI 33⚡ 效率工具 16
llama.cpp 背后的 C 语言张量库。
极速的现代分词器实现。
Fast and Accurate ML in 3 Lines of Code
A unified framework for machine learning with time series
Flax is a neural network library for JAX that is designed for flexibility.
A flexible, high-performance serving system for machine learning models
A scikit-learn compatible neural network library that wraps PyTorch
Supercharge Your Model Training
NVIDIA cuML: GPU-Accelerated Machine Learning
Simple and Distributed Machine Learning Python Library porting ML algorithms for Spark
Time series forecasting with PyTorch
High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.
A Rust machine learning framework.
Relax! Flux is the ML library that doesn't make you tensor
Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to p
Open-source library of optimized deep learning operations (matmul, convolution, attention) for CPUs (x64, AArch64, RISC-V) and Intel GPUs. Used by PyTorch, TensorFlow, OpenVINO, and ONNX Runtime.
A retargetable MLIR-based machine learning compiler and runtime toolkit.
Personal AI Notebooks. Organize files & webpages and generate notes from them. Open source, local & open data, open model choice (incl. local).
JAX-based neural network library
Deepnote is a drop-in replacement for Jupyter with an AI-first design, sleek UI, new blocks, and native data integrations. Use Python, R, and SQL locally in your favorite IDE, then scale to Deepnote cloud for real-time c
PyTorch native quantization for training and inference
Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/
Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.