#jupyter_notebook#ai#artificial_intelligence#chatgpt#deep_learning#from_scratch#gpt#language_model#large_language_models#llm#machine_learning#python#pytorch#transformer
You can learn how to build your own large language model (LLM) like GPT from scratch with clear, step-by-step guidance, including coding, training, and fine-tuning, all explained with examples and diagrams. This approach mirrors how big models like ChatGPT are made but is designed to run on a regular laptop without special hardware. You also get access to code for loading pretrained models and fine-tuning them for tasks like text classification or instruction following. This helps you deeply understand how LLMs work inside and lets you create your own functional AI assistant, gaining practical skills in AI development[1][2][3][4].
https://github.com/rasbt/LLMs-from-scratch
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