系统软件要求 操作系统:Linux(Ubuntu推荐) Python版本:3.8 或更高 CUDA:11.0 或更高 Flask(用于开发接口) torch(需要GPU支持的PyTorch) 分步指南 基础配置 以下是部署llama-cpp的基本步骤: 安装CUDA和cuDNN 从NVIDIA官网下载对应版本 按照官方指导完成安装 安装Python及必要依赖 使
model_path="./models/7B/llama-model.gguf", # n_gpu_layers=-1, # Uncomment to use GPU acceleration # seed=1337, # Uncomment to set a specific seed # n_ctx=2048, # Uncomment to increase the context window ) >>> output = llm( "Q: Name the planets in the solar system? A: ",...
如果您有 NVIDIA GPU 并希望使用 cuBLAS 后端,可以设置环境变量并安装: bash CMAKE_ARGS="-DLLAMA_CUBLAS=ON" pip install llama-cpp-python 在Windows 上,您可能还需要设置 FORCE_CMAKE=1: bash set FORCE_CMAKE=1 CMAKE_ARGS="-DLLAMA_CUBLAS=ON" pip install llama-cpp-python 从源码编译安装 如果...
Downloading ujson-5.10.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (9.3 kB) Collecting orjson>=3.2.1 (from fastapi>=0.100.0->llama_cpp_python==0.2.76) Using cached orjson-3.10.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (49 kB...
GPU:4060Ti-16G model gptq-no-desc-act gptq-desc-act awq gguf awq-gguf MMLU 0.5580 0.5912 0.5601 0.5597 0.5466 time 3741.81 3745.25 5181.86 3124.77 3091.46 目前还没有搞定gptq的gguf导出,后面会再尝试一下。 感谢以下博客: https://qwen.readthedocs.io/zh-cn/latest/index.html ...
>>>fromllama_cppimportLlama>>>llm=Llama(model_path="./models/7B/llama-model.gguf",# n_gpu_layers=-1, # Uncomment to use GPU acceleration# seed=1337, # Uncomment to set a specific seed# n_ctx=2048, # Uncomment to increase the context window)>>>output=llm("Q: Name the planets in...
CMAKE_ARGS="-DGGML_CUDA=on" FORCE_CMAKE=1 pip install 'llama-cpp-python[server]' python3 -m llama_cpp.server --model models/7B/llama-model.gguf --n_gpu_layers 35 Navigate to http://localhost:8000/docs to see the OpenAPI documentation. To bind to 0.0.0.0 to enable remote connect...
getpid() print('pid:', pid) pre_ram, pre_gpu = get_ram_usage(pid), get_gpu_usage(pid) print('pre_ram:', pre_ram, 'pre_gpu:', pre_gpu) func() post_ram, post_gpu = get_ram_usage(pid), get_gpu_usage(pid) print('post_ram:', post_ram, 'post_gpu:', post_gpu) return...
aria2c -x 16 -s 16 https://download.pytorch.org/whl/cu121/torch-2.5.0%2Bcu121-cp312-cp312-linux_x86_64.whl 实时查看nvidia显卡占用信息 : -n SECONDS:指定刷新间隔(默认是 2 秒)。 -d:高亮显示输出中变化的部分。 -t:不显示顶部的标题信息。
Windows 11 安装 llama-cpp-python,并启用 GPU 支持 直接安装,只支持CPU。想支持GPU,麻烦一些。 1. 安装CUDA Toolkit (NVIDIA CUDA Toolkit (available at https://developer.nvidia.com/cuda-downloads) 2. 安装如下物件: git python cmake Visual Studio Community (make sure you install this with the ...