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Repositories in this selection 12 · UTC 2026-11-03
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1—Ppytorch / pytorchA Python framework for tensors and neural networks.PythonNOASSERTION · Restricted / unknownInsufficient rank history105,08531,317——2026-11-02
2—Ttracel-ai / burnBurn is a next generation tensor library and Deep Learning Framework that doesn't compromise on flexibility, efficiency and portability.RustApache-2.0 · PermissiveInsufficient rank history16,2211,116——2026-11-02
3—Aapache / tvmOpen Machine Learning Compiler FrameworkPythonApache-2.0 · PermissiveInsufficient rank history13,8884,034——2026-11-03
4—Cchenyuntc / pytorch-bookPyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation ("Deep Learning Framework PyTorch: Getting Started and Practical Combat")Jupyter NotebookMIT · PermissiveInsufficient rank history12,8473,702——2023-12-24
5—Ccupy / cupyNumPy & SciPy for GPUPythonMIT · PermissiveInsufficient rank history12,3901,162——2026-11-03
6—Aarogozhnikov / einopsFlexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)PythonMIT · PermissiveInsufficient rank history9,630406——2026-08-26
7—Vvespa-engine / vespaThe AI search platformJavaApache-2.0 · PermissiveInsufficient rank history7,157750——2026-11-02
8—Ppytorch / executorchOn-device AI across mobile, embedded and edge for PyTorchPythonNOASSERTION · Restricted / unknownInsufficient rank history5,1511,235——2026-11-03
9—MMegEngine / MegEngineMegEngine is a fast, scalable, easy-to-use deep learning framework that supports automatic derivationC++Apache-2.0 · PermissiveInsufficient rank history4,809543——2024-10-24
10—Hhosseinmoein / DataFrameC++ DataFrame for statistical, financial, and ML analysis in modern C++C++BSD-3-Clause · PermissiveInsufficient rank history2,997363——2026-11-02
11—Uunslothai / hyperlearnAuthor description: 2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.Jupyter NotebookApache-2.0 · PermissiveInsufficient rank history2,529170——2024-11-19
12—Aashvardanian / NumKongSIMD-accelerated distances, dot products, matrix ops, geospatial & geometric kernels for 16 numeric types — from 6-bit floats to 64-bit complex — across x86, Arm, RISC-V, and WASM, with bindings for Python, Rust, C, C++, Swift, JS, and Go 📐CApache-2.0 · PermissiveInsufficient rank history1,905141——2026-10-31
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