# 54_llm_projs **Repository Path**: linux2014/54_llm_projs ## Basic Information - **Project Name**: 54_llm_projs - **Description**: No description available - **Primary Language**: Unknown - **License**: Not specified - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2024-03-06 - **Last Updated**: 2024-03-14 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README --- --- ### 大模型 ### Git pull(拉取),push(上传)命令整理(详细) https://www.cnblogs.com/jpfss/p/12084797.html https://zhuanlan.zhihu.com/p/613810247?utm_id=0 https://www.cnblogs.com/yinzhi/p/11599997.html https://www.thepaper.cn/newsDetail_forward_26533310 --- ### 优质开源项目总结 https://github.com/OpenGithubs https://open.itc.cn/ https://github.com/OpenEmu/OpenEmu https://open.itc.cn/?tab=repos https://open.itc.cn/github/collection/detail?collectionId=01HNEKV7KCN0VKQ8MX8AXSB5T3 https://open.itc.cn/github/collection/detail?collectionId=01HEA0CBBHSW7FGS2G3WCHA4NN ### 实时向量搜索引擎: https://github.com/vearch/gamma --- --- gpt4free: https://blog.csdn.net/qq_35811830/article/details/130517022 https://blog.csdn.net/AI_SHELL/article/details/136370557 GPT-4的白嫖方法及其典型应用 https://zhuanlan.zhihu.com/p/653184649 GPT推出高级数据分析功能 https://mp.weixin.qq.com/s/iVEAGjpWZDwyARjgLLPy_g 用ChatGPT神器Code Interpreter做市场研究和数据分析 - 到底行不行? https://mp.weixin.qq.com/s/jZCOxlut2HPQf-EyKJFEXA --- 大语言模型案例: https://openai.com/ https://openai.com/blog/chatgpt https://zhuanlan.zhihu.com/p/667077454?utm_id=0 ChatGPT保姆级教程,一分钟学会使用ChatGPT! https://juejin.cn/post/7198097078005841980 chatgpt 文心一言 通意千问 github copilot Code GeeX 学堂在线 比心云 翻墙:自行购买服务或在外网服务器搭建; 大模型: https://zhuanlan.zhihu.com/p/647220145 https://zhuanlan.zhihu.com/p/676432440 https://zhuanlan.zhihu.com/p/676201455 https://zhuanlan.zhihu.com/p/684544418 https://juejin.cn/post/7314135212354404363 https://www.zhihu.com/question/608820310 https://zhuanlan.zhihu.com/p/630577059 https://www.zhihu.com/question/623672939/answers/updated https://www.zhihu.com/question/635910343 https://zhuanlan.zhihu.com/p/674925860 https://mp.weixin.qq.com/s?__biz=MzUyOTA5OTcwMg==&mid=2247484879&idx=1&sn=9babf498e543f41ff16b37a3baf63b65&scene=21#wechat_redirect ### 深度学习 https://open.itc.cn/github/collection/detail?collectionId=01HNEM074CN281BV551K33X5C1 ### redis技术栈 https://open.itc.cn/github/collection/detail?collectionId=01H162C1X10VD5MEFHR8SB3TA8 --- https://github.com/mlabonne/llm-course https://github.com/ninehills/blog https://gitee.com/oschina/awesome-llm --- https://github.com/microsoft/playwright-python https://github.com/xszyou/Fay https://github.com/google/gemma.cpp https://github.com/google/gemma_pytorch https://github.com/Z4nzu/hackingtool https://github.com/ByteByteGoHq/system-design-101 https://github.com/WisdomShell/codeshell https://github.com/thewhiteh4t/seeker https://github.com/xiangsx/gpt4free-ts https://github.com/doocs/leetcode https://github.com/morph-labs/rift https://github.com/modelscope/facechain https://github.com/LlamaFamily/Llama-Chinese https://github.com/ollama/ollama https://github.com/lllyasviel/Fooocus https://github.com/karpathy/llama2.c https://github.com/mlc-ai/mlc-llm https://github.com/sunner/ChatALL https://github.com/xtekky/gpt4free --- https://github.com/NaiboWang/EasySpider https://github.com/AI4Finance-Foundation/FinGPT https://github.com/krahets/hello-algo https://github.com/netdata/netdata https://github.com/isocpp/CppCoreGuidelines https://github.com/hehonghui/awesome-english-ebooks https://github.com/geekan/MetaGPT https://github.com/bradtraversy/50projects50days https://github.com/vim/vim --- https://github.com/chuyangliu/snake --- ### python docs/python.md https://docs.python.org/3.7/tutorial/venv.html To create a virtual environment, decide upon a directory where you want to place it, and run the venv module as a script with the directory path: python3 -m venv tutorial-env This will create the tutorial-env directory if it doesn’t exist, and also create directories inside it containing a copy of the Python interpreter, the standard library, and various supporting files. Once you’ve created a virtual environment, you may activate it. On Windows, run: tutorial-env\Scripts\activate.bat On Unix or MacOS, run: source tutorial-env/bin/activate Activating the virtual environment will change your shell’s prompt to show what virtual environment you’re using, and modify the environment so that running python will get you that particular version and installation of Python. For example: ``` $ source ~/envs/tutorial-env/bin/activate (tutorial-env) $ python Python 3.5.1 (default, May 6 2016, 10:59:36) ... >>> import sys >>> sys.path ['', '/usr/local/lib/python35.zip', ..., '~/envs/tutorial-env/lib/python3.5/site-packages'] >>> ``` ou can install, upgrade, and remove packages using a program called pip. By default pip will install packages from the Python Package Index, . You can browse the Python Package Index by going to it in your web browser, or you can use pip’s limited search feature: (tutorial-env) $ pip search astronomy skyfield - Elegant astronomy for Python gary - Galactic astronomy and gravitational dynamics. novas - The United States Naval Observatory NOVAS astronomy library astroobs - Provides astronomy ephemeris to plan telescope observations PyAstronomy - A collection of astronomy related tools for Python. ... pip has a number of subcommands: “search”, “install”, “uninstall”, “freeze”, etc. (Consult the Installing Python Modules guide for complete documentation for pip.) You can install the latest version of a package by specifying a package’s name: (tutorial-env) $ pip install novas Collecting novas Downloading novas-3.1.1.3.tar.gz (136kB) Installing collected packages: novas Running setup.py install for novas Successfully installed novas-3.1.1.3 You can also install a specific version of a package by giving the package name followed by == and the version number: (tutorial-env) $ pip install requests==2.6.0 Collecting requests==2.6.0 Using cached requests-2.6.0-py2.py3-none-any.whl Installing collected packages: requests Successfully installed requests-2.6.0 pip show will display information about a particular package: pip list will display all of the packages installed in the virtual environment: pip freeze will produce a similar list of the installed packages, but the output uses the format that pip install expects. A common convention is to put this list in a requirements.txt file: (tutorial-env) $ pip freeze > requirements.txt (tutorial-env) $ cat requirements.txt novas==3.1.1.3 numpy==1.9.2 requests==2.7.0 The requirements.txt can then be committed to version control and shipped as part of an application. Users can then install all the necessary packages with install -r: (tutorial-env) $ pip install -r requirements.txt Collecting novas==3.1.1.3 (from -r requirements.txt (line 1)) ... Collecting numpy==1.9.2 (from -r requirements.txt (line 2)) ... Collecting requests==2.7.0 (from -r requirements.txt (line 3)) ... Installing collected packages: novas, numpy, requests Running setup.py install for novas Successfully installed novas-3.1.1.3 numpy-1.9.2 requests-2.7.0 删除虚拟环境实例: python -m venv --clear my_venv_gpt4 清理pip缓存: pip cache purge --- pip安装的可执行文件都在python/Scripts目录下,也就是python安装目录下的Scripts文件夹内; --- ### pip https://pip.pypa.io/en/stable/getting-started/ --- ---