#jupyter_notebook#chatglm#chatglm3#gemma_2b_it#glm_4#internlm2#llama3#llm#lora#minicpm#q_wen#qwen#qwen1_5#qwen2
This guide helps beginners set up and use open-source large language models (LLMs) on Linux or cloud platforms like AutoDL, with step-by-step instructions for environment setup, model deployment, and fine-tuning for models such as LLaMA, ChatGLM, and InternLM[2][4][5]. It covers everything from basic installation to advanced techniques like LoRA and distributed fine-tuning, and supports integration with tools like LangChain and online demo deployment. The main benefit is making powerful AI models accessible and easy to use for students, researchers, and anyone interested in experimenting with or customizing LLMs for their own projects[2][4][5].
https://github.com/datawhalechina/self-llm
https://mborgerson.com/creating-an-executable-from-a-python-script/
Creating an Executable from a Python Script
Python is one of my favorite programming languages. That being said, if you've ever had to deploy an application written in Python then you know just how painful it can be.
#PyInstaller
http://www.pyinstaller.org/
#PyInstaller is a program that #freezes (#packages) Python programs into #stand_alone#executables, under Windows, Linux, Mac OS X, FreeBSD, Solaris and AIX. Its main advantages over similar tools are that PyInstaller works with Python 2.7 and 3.3—3.5, it builds smaller executables thanks to transparent compression, it is fully multi-platform, and use the OS support to load the dynamic libraries, thus ensuring full compatibility.
https://www.infoworld.com/article/3230202/python/6-essential-libraries-for-every-python-developer.html
6 essential libraries for every Python developer
Whether you're compiling Python for speed, building native UIs for Python desktop apps, or refining existing Python code, these Python projects have you covered
Python has seen wide adoption across industries and disciplines by dint of being easy to work with. But it has also been aided by a wealth of third-party projects—libraries, add-ons, and complementary development efforts—that extend the language to an ever widening range of use cases.
#PyPy
#CFFI(C Foreign Function Interface library)
#PyInstaller
#PBR(Python Build Reasonableness)
#WxPython
#Mypy