Open Source Threat Intelligence Platform
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Open Source Threat Intelligence Platform
TranslatedLet AI turn your editing into a JianYing (剪映) draft, then keep editing it in JianYing · AI → editable JianYing (剪映) drafts on macOS
Modular, fast NLP framework, compatible with Pytorch and spaCy, offering tailored support for French clinical notes.
Manga / black & white comic filter for ComfyUI: crisp lines, flat tones, real screentone (halftone), solid blacks and panel frames.
Trading environnement for RL agents, backtesting and training.
Modern honeypot supporting multiple services, realistic website cloning, and AI-powered features
Generate graphs and charts based on password cracking result
PhysAg3D: Bridging 3D Generative and Agentic Models for High-Fidelity and Physically-Interactive Assets
Build autonomous AI agents that interact with blockchains — in minutes, not months.
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Zeline — an open-source agentic AI framework developed by Zerolinear.
AI-assisted Windows and Chrome GUI delegation for Codex: task contracts, local execution, Jev semantic decisions, recovery and outcome verification.
A coherent Ansible roles collection to simply deploy clusters of nodes.
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Flake8 Type Annotation Checking
MicroPython I2C driver for MPU9250 9-axis motion tracking device
OpenBioLink is a resource and evaluation framework for evaluating link prediction models on heterogeneous biomedical graph data.
A Genetic Programming platform for Python with TensorFlow for wicked-fast CPU and GPU support.
Free YouTube views booster and channel growth tool. Increase video views, watch time and engagement with smart delivery system. Easy to use, fully configurable, safe mode included.
A tool for quantitative risk analysis of Android applications based on machine learning techniques
Public repository for improvements to the EXTRABACON exploit
LLM for Drug Editing, ICLR 2024
Sample skills, scripts, and reference workflows for AI-assisted planning, setup, and configuration of Oracle Fusion Cloud Applications.
This repository contains codes for the paper entitled "A CNN-RNN Framework for Crop Yield Prediction"