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: ",...
对于Linux用户,通常需要安装build-essential、cmake、ninja-build等编译工具。 安装依赖库: 确保安装了Python和pip。 根据你的系统配置,可能需要安装特定的BLAS后端(如OpenBLAS、cuBLAS)来加速计算。 使用正确的安装命令: 根据你的系统环境和硬件配置,选择合适的安装命令。例如,如果你使用的是MacOS且希望启用Metal GPU加速...
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...
量化:4bit 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 来源...
>>>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...
Hi everyone ! I have spent a lot of time trying to install llama-cpp-python with GPU support. I need your help. I'll keep monitoring the thread and if I need to try other options and provide info post and I'll send everything quickly. I ...
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 ...
Similar to Hardware Acceleration section above, you can also install with GPU (cuBLAS) support like this: 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 ...
>>>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...