关于using cached的问题

可以参看这个博客

https://stackoverflow.com/questions/9510474/removing-pips-cache

(xinference) PS C:\Windows\system32> pip install llama-cpp-python Collecting llama-cpp-python Using cached llama_cpp_python-0.3.7.tar.gz (66.7 MB) Installing build dependencies ... done Getting requirements to build wheel ... done Installing backend dependencies ... done Preparing metadata (pyproject.toml) ... done Collecting typing-extensions>=4.5.0 (from llama-cpp-python) Using cached typing_extensions-4.12.2-py3-none-any.whl.metadata (3.0 kB) Collecting numpy>=1.20.0 (from llama-cpp-python) Using cached numpy-2.2.3-cp311-cp311-win_amd64.whl.metadata (60 kB) Collecting diskcache>=5.6.1 (from llama-cpp-python) Using cached diskcache-5.6.3-py3-none-any.whl.metadata (20 kB) Collecting jinja2>=2.11.3 (from llama-cpp-python) Using cached jinja2-3.1.5-py3-none-any.whl.metadata (2.6 kB) Collecting MarkupSafe>=2.0 (from jinja2>=2.11.3->llama-cpp-python) Using cached MarkupSafe-3.0.2-cp311-cp311-win_amd64.whl.metadata (4.1 kB) Using cached diskcache-5.6.3-py3-none-any.whl (45 kB) Using cached jinja2-3.1.5-py3-none-any.whl (134 kB) Using cached numpy-2.2.3-cp311-cp311-win_amd64.whl (12.9 MB) Using cached typing_extensions-4.12.2-py3-none-any.whl (37 kB) Using cached MarkupSafe-3.0.2-cp311-cp311-win_amd64.whl (15 kB) Building wheels for collected packages: llama-cpp-python Building wheel for llama-cpp-python (pyproject.toml) ... error error: subprocess-exited-with-error × Building wheel for llama-cpp-python (pyproject.toml) did not run successfully. │ exit code: 1 ╰─> [306 lines of output] *** scikit-build-core 0.11.0 using CMake 3.31.6 (wheel) *** Configuring CMake... 2025-03-04 00:24:37,103 - scikit_build_core - WARNING - Can't find a Python library, got libdir=None, ldlibrary=None, multiarch=None, masd=None loading initial cache file C:\Users\admin\AppData\Local\Temp\tmphkbm01o4\build\CMakeInit.txt -- Building for: Visual Studio 17 2022 -- Selecting Windows SDK version 10.0.22621.0 to target Windows 10.0.1
最新发布
03-08
评论
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值