mirror of
https://github.com/ggml-org/llama.cpp.git
synced 2026-08-12 22:31:11 +04:00
ruanslvandGitHub
0b1bad14ff
* chat : fix muse-glimmer swallowing a trailing tool call into content
Muse Glimmer routinely answers the user and calls a tool in a single
generation. The template terminates a message with <|eom|> when more
messages follow in the same turn and <|eot|> only at the end of the turn,
so the answer is closed by <|eom|> and the call opens a fresh header:
<prose><|eom|><|start|>assistant to=<tool><|message|><atem:function_calls>...
The final-message rule read content with until("<|eot|>"), which assumed the
user-facing message is always last. There is no <|eot|> before the call, so
content ran to the end of the turn, absorbed the markup, and no tool_calls
were emitted - the tool never ran. On a tau2-bench telecom run this hit 43
turns across 19 of 114 tasks.
Stop the answer at <|eom|> and parse what follows as tool calls.
Adds models/templates/muse-glimmer.jinja and four parser tests: a plain
answer, the <|eom|> junction, markup quoted in an answer staying content,
and tool markup inside the to=self channel staying reasoning.
* address comment
llama.cpp
LLM inference in C/C++
manifesto / ggml / ops / maintainer PRs / compile times / lib llama API / llama-server REST API
Quick start
A few options to get llama.cpp installed on your machine:
- Visit https://llama.app and follow the instructions
- Run with Docker - see our Docker documentation
- Download pre-built binaries from the releases page
- Build from source by cloning this repository - check out our build guide
Once installed:
# Download and run a model directly from Hugging Face
llama cli -hf ggml-org/Qwen3.5-0.8B-GGUF
# Launch OpenAI-compatible API server
llama serve -hf ggml-org/Qwen3.5-0.8B-GGUF
|
|
|
Description
The main goal of llama.cpp is to enable LLM (and VLM) 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
- RVV, ZVFH, ZFH, ZICBOP and ZIHINTPAUSE support for RISC-V 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 GPUs via MUSA)
- Vulkan and SYCL backend support
- CPU+GPU hybrid inference to partially accelerate models larger than the total VRAM capacity
The llama.cpp project is build on top of the ggml library.
Supported backends
| Backend | Target devices |
|---|---|
| BLAS | All |
| BLIS | All |
| CANN | Ascend NPU |
| CUDA | Nvidia GPU |
| HIP | AMD GPU |
| Hexagon [In Progress] | Snapdragon |
| IBM zDNN | IBM Z & LinuxONE |
| MUSA | Moore Threads GPU |
| Metal | Apple Silicon |
| OpenCL | Adreno GPU |
| OpenVINO [In Progress] | Intel CPUs, GPUs, and NPUs |
| RPC | All |
| SYCL | Intel GPU |
| VirtGPU | VirtGPU APIR |
| Vulkan | GPU |
| WebGPU | All |
| ZenDNN | AMD CPU |
Documentation
Tools
Development
- How to build
- Running on Docker
- Build on Android
- Multi-GPU usage
- Performance troubleshooting
- GGML tips & tricks
- XCFramework
- Completions
- Models
Contributing
- Contributors can open PRs
- Collaborators will be invited based on contributions
- Maintainers can push to branches in the
llama.cpprepo and merge PRs into themasterbranch - Any help with managing issues, PRs and projects is very appreciated!
- Read the CONTRIBUTING.md for more information
Acknowledgements
- yhirose/cpp-httplib - Single-header HTTP server, used by
llama-server- MIT license - stb-image - Single-header image format decoder, used by multimodal subsystem - Public domain
- nlohmann/json - Single-header JSON library, used by various tools/examples - MIT License
- miniaudio.h - Single-header audio format decoder, used by multimodal subsystem - Public domain
- subprocess.h - Single-header process launching solution for C and C++ - Public domain