Tensor library for machine learning
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正在載入完整 README。 以下為已儲存的摘錄。
For a minimal, fully commented example (matrix multiplication), see examples/simple.
The main goal of ggml is to be a simple, portable, and efficient tensor library for machine learning with minimal setup.
• Plain C/C++ implementation without any dependencies
• Cross-platform - x86, ARM, RISC-V, LoongArch, PowerPC, s390x, and WebAssembly
• SIMD-optimized kernels for x86, ARM, and RISC-V
• Broad backend support - CPU, GPU, NPU, and browser
• 2- to 8-bit integer quantization, plus MXFP4 and NVFP4 microscaling formats
• Zero memory allocations during runtime檢視完整 README ↗Tensor library for machine learning
Build from source:
git clone https://github.com/ggml-org/ggml
cd ggml
mkdir build && cd build
cmake ..
cmake --build . --config Release -j 8
For a minimal, fully commented example (matrix multiplication), see examples/simple.
The main goal of ggml is to be a simple, portable, and efficient tensor library for machine learning with minimal setup.
ggml library (including to the CMake build system), please open a PR in llama.cpp - doing so will make your PR more visible, better tested, and more likely to be reviewed