pip install llama-cpp-python \ --extra-index-url=https://abetlen.github.io/llama-cpp-python/whl/cu121 将cu121替换为你具体使用的CUDA版本标识符。 使用Metal(MPS) 若你的系统基于MacOS并且版本在11.0以上,则可以启用Metal以提高性能。在此之前,设置相应的环境变量: export CMAKE_ARGS="-DGGML_METAL=...
v0.2.89-cu121 Compare github-actionsreleased this19 Aug 18:43 ·107 commitsto main since this release v0.2.89-cu121 d7328ef Assets6 llama_cpp_python-0.2.89-cp310-cp310-linux_x86_64.whl 380 MB2024-08-19T18:43:17Z llama_cpp_python-0.2.89-cp311-cp311-linux_x86_64.whl ...
Python Version is 3.10, 3.11 or 3.12 pip install llama-cpp-python \ --extra-index-url https://abetlen.github.io/llama-cpp-python/whl/<cuda-version> Where <cuda-version> is one of the following: cu121: CUDA 12.1 cu122: CUDA 12.2 cu123: CUDA 12.3 cu124: CUDA 12.4 For example, to...
uv pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121 没有全局代理加速的情况: 先用代理加速去下载torch-2.3.1+cu121-cp311-cp311-win_amd64.whl uv pip install .\torch-2.3.1+cu121-cp311-cp311-win_amd64.whl uv pip install torchvision==0.18.1+cu1...
pip3 install torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121 pip install llmtuner 2 下载可微调的模型 创建用于存放模型的文件夹,取名为models 将llama3 8b的模型文件项目下载到此处。下载时间稍微有点长,请耐心等待 git clone https://www.modelscope.cn/LLM-Research/Meta-Llama...
先用代理加速去下载torch-2.3.1+cu121-cp311-cp311-win_amd64.whl uv pip install .\torch-2.3.1+cu121-cp311-cp311-win_amd64.whl uv pip install torchvision==0.18.1+cu121 torchaudio==2.3.1+cu121 -f https://download.pytorch.org/whl/torch_stable.html ...
编译好以后,把llama.cpp\build\bin\release目录下的所有文件复制到llama.cpp目录下 激活虚拟环境 打开cmd conda activate env_name 安装依赖包 在env_name的虚拟环境中逐个输入以下指令 pip install torch==2.2.2--index-url https://download.pytorch.org/whl/cu121 ...
那么，llama.cpp 有何优势呢？无需任何额外依赖，相比 Python 代码对 PyTorch 等库的要求，C/C++ 直接...
env# 安装依赖包pipinstalltorch==2.2.2--index-urlhttps://download.pytorch.org/whl/cu121pip...
pip install --upgrade pip pip install “sglang[all]” # 安装FlashInfer CUDA库 pip install flashinfer -i https://flashinfer.ai/whl/cu121/torch2.3/ 要启动服务器,请运行如下命令: # 命令占位符 ! python -m sglang.launch_server --model-path Qwen/Qwen2-1.5B-Instruct --port 30000 vllm的关...