How Pytorch Powers Training Inference

Learn about new PyTorch advancements for LLMs and how PyTorch is enhancing every aspect of the LLM lifecycle.

https://www.youtube.com/watch?v=96VIEJfhUBg

csv_trimming

Python package to remove common ugliness from a csv-like file

https://github.com/LucaCappelletti94/csv_trimming

LitServe

Lightning-fast serving engine for AI models. Flexible. Easy. Enterprise-scale.

https://github.com/Lightning-AI/LitServe

django-cotton

Bringing component based design to Django templates.

https://github.com/wrabit/django-cotton

Why I Still Use Python Virtual Environments in Docker

The article argues for using Python virtual environments in Docker containers, citing benefits like predictability, standardization, and easier debugging. The author contends that virtual environments provide a consistent, well-understood structure for Python applications, making communication and deployment across teams more straightforward, while also simplifying Python's import behavior.

https://hynek.me/articles/docker-virtualenv/

Maximizing Python Code Efficiency: Strategies to Overcome Common Performance Hurdles

This article talks about performance issues caused by nested loops and memory allocation issues. It provides strategies to overcome these issues while improving efficiency.

https://towardsdatascience.com/maximizing-python-code-efficiency-strategies-to-overcome-common-performance-hurdles-c6292610d785

kotaemon

An open-source RAG-based tool for chatting with your documents.

https://github.com/Cinnamon/kotaemon

Taming the beast that is the Django ORM - An introduction

The Django ORM, how it compares to raw SQL and gotchas that you should be aware of when using it

https://www.davidhang.com/blog/2024-09-01-taming-the-django-orm/

Building LLMs from the Ground Up

This tutorial guides coders through the fundamentals of large language models (LLMs), explaining how they work and how to build them from scratch in PyTorch. It covers coding a small GPT-like model, its data pipeline, architecture, pretraining, and fine-tuning using open-source libraries.

https://www.youtube.com/watch?v=quh7z1q7-uc

supertree

supertree is a Python package designed to visualize decision trees in an interactive and user-friendly way within Jupyter Notebooks, Jupyter Lab, Google Colab, and any other notebooks that support HTML rendering.

https://github.com/mljar/supertree

uvtrick

A fun party trick to run Python code from another venv into this one.

https://github.com/koaning/uvtrick

Multimodal Data Analysis with LLMs and Python – Tutorial

The tutorial teaches how to analyze multimodal data using Large Language Models (LLMs) and Python, covering text classification, image-based question answering, audio transcription, and creating a natural language query interface for SQL databases.

https://www.youtube.com/watch?v=3-4qAkFRpAk

Classifying all of the pdfs on the internet

The article describes an attempt to classify a massive dataset of 8.4 million PDFs from Common Crawl using various machine learning techniques. The author experiments with different approaches, including deep learning models and traditional machine learning methods like XGBoost, ultimately achieving the best performance with an XGBoost model trained on embeddings, reaching 85.26% accurac...

https://snats.xyz/pages/articles/classifying_a_bunch_of_pdfs.html

Mini-Omni

Mini-Omni is an open-source multimodel large language model that can hear, talk while thinking. Featuring real-time end-to-end speech input and streaming audio output conversational capabilities.

https://github.com/gpt-omni/mini-omni