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Python GUIs for Humans! PySimpleGUI is the top-rated Python application development environment. Launched in 2018 and actively developed, maintained, and supported in 2024. Transforms tkinter, Qt, …
The pytest framework makes it easy to write small tests, yet scales to support complex functional testing
A modern and customizable python UI-library based on Tkinter
Install and Run Python Applications in Isolated Environments
This project aim to reproduce Sora (Open AI T2V model), we wish the open source community contribute to this project.
A cross-platform GUI automation Python module for human beings. Used to programmatically control the mouse & keyboard.
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
Private chat with local GPT with document, images, video, etc. 100% private, Apache 2.0. Supports oLLaMa, Mixtral, llama.cpp, and more. Demo: https://gpt.h2o.ai/ https://gpt-docs.h2o.ai/
Statsmodels: statistical modeling and econometrics in Python
YOLOv10: Real-Time End-to-End Object Detection [NeurIPS 2024]
NumPy aware dynamic Python compiler using LLVM
An API standard for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)
StreamDiffusion: A Pipeline-Level Solution for Real-Time Interactive Generation
Library for building powerful interactive command line applications in Python
A framework to enable multimodal models to operate a computer.
Hydra is a framework for elegantly configuring complex applications
Implementation of Nougat Neural Optical Understanding for Academic Documents
Code for the paper Hybrid Spectrogram and Waveform Source Separation
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
Bayesian Modeling and Probabilistic Programming in Python
A unified framework for machine learning with time series
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
A python library for user-friendly forecasting and anomaly detection on time series.
Deep universal probabilistic programming with Python and PyTorch
Reads key-value pairs from a .env file and can set them as environment variables. It helps in developing applications following the 12-factor principles.