Tensor Collection

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🔮Psychic

★★★★★

“Tensors and Dynamic neural networks in Python with strong GPU acceleration”

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⚙️Steel

★★★

“Burn is a next generation tensor library and Deep Learning Framework that doesn't compromise on flexibility, efficiency and portability.”

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🔮Psychic

★★★

“Open Machine Learning Compiler Framework”

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📦Normal

★★★

“PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch：入门与实战》)”

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🔮Psychic

★★★

“NumPy & SciPy for GPU”

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🔮Psychic

★★★

“Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)”

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⚡Thunder

★★★

“The AI search platform”

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🔥Fire

★★

“MegEngine 是一个快速、可拓展、易于使用且支持自动求导的深度学习框架”

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🔮Psychic

★★

“On-device AI across mobile, embedded and edge for PyTorch”

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⚡Thunder

★★

“LibRec: A Leading Java Library for Recommender Systems, see”

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🔥Fire

★★

“C++ DataFrame for statistical, financial, and ML analysis in modern C++”

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✨Fairy

★★

“Multi-dimensional arrays (tensors) and numerical definitions for Elixir”

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📦Normal

★★

“A list of awesome compiler projects and papers for tensor computation and deep learning.”

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🔮Psychic

★★

“Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.”

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📦Normal

★★

“2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.”

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📦Normal

★★

“Inference Llama 2 in one file of pure 🔥”

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⚙️Steel

★★

“Deep learning in Rust, with shape checked tensors and neural networks”

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⚔️Fighting

★★

“SIMD-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 📐”