Popular GitHub Repositories for Red Hen Labs

所有系统提示都需透明公开

Test your prompts, agents, and RAGs. Red teaming, pentesting, and vulnerability scanning for LLMs. Compare performance of GPT, Claude, Gemini, Llama, and more. Simple declarative configs with command line and CI/CD integration.

An 11-Lesson course teaching everything you need to know about harnessing GitHub Copilot as an AI Paired Programming resource.

Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams

? Open-Source Evaluation & Testing for AI & LLM systems

TensorFlow Basic Tutorial Labs

The Python Risk Identification Tool for generative AI (PyRIT) is an open source framework built to empower security professionals and engineers to proactively identify risks in generative AI systems.

Agentic LLM Vulnerability Scanner / AI red teaming kit ?

A secure sandbox environment for malware developers and red teamers to test payloads against detection mechanisms before deployment. Integrates with LLM agents via MCP for enhanced analysis capabilities.

Visually build a full featured chat bot for Telegram, Facebook Messenger, Whatsapp and Slack with Node-RED. Almost no coding skills required.

Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework

Rigorously test, monitor, and optimize agent systems—grounded in research from Stanford and Berkeley AI Labs.

A security scanner for your LLM agentic workflows

Useful links of different content related to AI, Computer Vision, and Robotics.

Implementation of Band Split Roformer, SOTA Attention network for music source separation out of ByteDance AI Labs

The Fuzzy Labs guide to the universe of open source MLOps

A script for credentials-based attack surface enumeration and general reconnaissance of massive networks

This repo contains the updated version of all the assignments/labs (done by me) of Deep Learning Specialization on Coursera by Andrew Ng. It includes building various deep learning models from scratch and implementing them for object detection, facial recognition, autonomous driving, neural machine translation, trigger word detection, etc.

Implementations of the algorithms described in Differentiable plasticity: training plastic networks with gradient descent, a research paper from Uber AI Labs.

This project is a digital human that can talk and listen to you. It uses OpenAI's GPT to generate responses, OpenAI's Whisper to transcript the audio, Eleven Labs to generate voice and Rhubarb Lip Sync to generate the lip sync.