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[ sid ]
[ ソース: llama.cpp ]
パッケージ: libllama0 (5882+dfsg-3)
LLM inference in C/C++ - libraries
The main goal of llama.cpp is to enable LLM inference with minimal setup and state-of-the-art performance on a wide range of hardware - locally and in the cloud.
* Plain C/C++ implementation without any dependencies * Apple silicon is a first-class citizen - optimized via ARM NEON, Accelerate and Metal frameworks * AVX, AVX2, AVX512 and AMX support for x86 architectures * 1.5-bit, 2-bit, 3-bit, 4-bit, 5-bit, 6-bit, and 8-bit integer quantization for faster inference and reduced memory use * Custom CUDA kernels for running LLMs on NVIDIA GPUs (support for AMD GPUs via HIP and Moore Threads MTT GPUs via MUSA) * Vulkan and SYCL backend support * CPU+GPU hybrid inference to partially accelerate models larger than the total VRAM capacity
The compute functionality is provided by ggml. By default, ggml's CPU backend is installed, but there are many other backends for CPUs and GPUs.
This package contains the libllama and libmtmd libraries. Note that these libraries are not yet stable, so they are installed to private directories for now.
その他の libllama0 関連パッケージ
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- dep: libc6 (>= 2.38)
- GNU C ライブラリ: 共有ライブラリ
以下のパッケージによって提供される仮想パッケージでもあります: libc6-udeb
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- dep: libgcc-s1 (>= 3.0) [riscv64 以外]
- GCC 共有ライブラリ
- dep: libgcc-s1 (>= 4.3) [riscv64]
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- dep: libggml0 (>= 0.0~git20250712.d62df60)
- Tensor library for machine learning - libraries
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- dep: libggml0-backend-cpu (<< 0.0~git20250713)
- Tensor library for machine learning - CPU backend
- dep: libggml0-backend-cpu (>= 0.0~git20250712)
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- dep: libstdc++6 (>= 11)
- GNU 標準 C++ ライブラリ v3