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An opinionated list of awesome Python frameworks, libraries, software and resources.
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
A list of useful payloads and bypass for Web Application Security and Pentest/CTF
scikit-learn: machine learning in Python
The Big List of Naughty Strings is a list of strings which have a high probability of causing issues when used as user-input data.
Streamlit — A faster way to build and share data apps.
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
The fundamental package for scientific computing with Python.
⚡ A Fast, Extensible Progress Bar for Python and CLI
🗃 Open source self-hosted web archiving. Takes URLs/browser history/bookmarks/Pocket/Pinboard/etc., saves HTML, JS, PDFs, media, and more...
The open source developer platform to build AI agents and models with confidence. Enhance your AI applications with end-to-end tracking, observability, and evaluations, all in one integrated platform.
The official Python SDK for Model Context Protocol servers and clients
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
Faker is a Python package that generates fake data for you.
DeerFlow is a community-driven Deep Research framework, combining language models with tools like web search, crawling, and Python execution, while contributing back to the open-source community.
Tongyi Deep Research, the Leading Open-source Deep Research Agent
Datasets, Transforms and Models specific to Computer Vision
SpiderFoot automates OSINT for threat intelligence and mapping your attack surface.
pix2tex: Using a ViT to convert images of equations into LaTeX code.
RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7 "Goose". So it's combining the best of RN…
The pytest framework makes it easy to write small tests, yet scales to support complex functional testing
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.