Paket: libllama0 (5882+dfsg-3)

Links für libllama0

Debian-Ressourcen:

Quellcode-Paket llama.cpp herunterladen:

Betreuer:

Externe Ressourcen:

Homepage [github.com]

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.

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dep: libc6 (>= 2.38)

GNU-C-Bibliothek: Laufzeitbibliotheken
auch ein virtuelles Paket, bereitgestellt durch libc6-udeb
dep: libgcc-s1 (>= 3.0) [nicht riscv64]

GCC Support-Bibliothek

dep: libgcc-s1 (>= 4.3) [riscv64]
dep: libggml0 (>= 0.0~git20250712.d62df60)

Tensor library for machine learning - libraries
dep: libggml0-backend-cpu (<< 0.0~git20250713)

Tensor library for machine learning - CPU backend

dep: libggml0-backend-cpu (>= 0.0~git20250712)
dep: libstdc++6 (>= 11)

GNU-Implementierung der Standard-C++-Bibliothek (Version 3)

libllama0 herunterladen

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arm64	646,2 kB	2.472,0 kB	[Liste der Dateien]
ppc64el	731,0 kB	2.856,0 kB	[Liste der Dateien]
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