-
Automizei
- MaringΓ‘, ParanΓ‘, Brazil
- in/juliano-donini
Starred repositories
π Freely available programming books
An opinionated list of awesome Python frameworks, libraries, software and resources.
The official gpt4free repository | various collection of powerful language models | o4, o3 and deepseek r1, gpt-4.1, gemini 2.5
The world's simplest facial recognition api for Python and the command line
Build and share delightful machine learning apps, all in Python. π Star to support our work!
Python packaging and dependency management made easy
Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
Write scalable load tests in plain Python ππ¨
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
Download your Spotify playlists and songs along with album art and metadata (from YouTube if a match is found).
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python
A configuration framework that enhances Claude Code with specialized commands, cognitive personas, and development methodologies.
Typer, build great CLIs. Easy to code. Based on Python type hints.
Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.
The interactive graphing library for Python β¨
Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
An orchestration platform for the development, production, and observation of data assets.
Image augmentation for machine learning experiments.
GenAI Agent Framework, the Pydantic way
Beta release of Archon OS - the knowledge and task management backbone for AI coding assistants.
Cleanlab's open-source library is the standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.