The Generative AI Landscape provides machine-learning models, research, training resources, or evaluation tools.
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Deploy a ML inference service on a budget in less than 10 lines of code.
Train and run a computer vision model with 5-10 lines of code.
Testing framework dedicated to ML models, from tabular to LLMs. Detect risks of biases, performance issues and errors in 4 lines of code.
LLM App is a Python library that helps you build real-time AI-powered data pipelines with few lines of code.
Ultra-lightweight personal AI assistant framework (~4,000 lines of Python). Supports MCP, 9+ chat channels, and extensible skills system.
Open-source Python library designed to make it extremely easy to build and run agents using just a few lines of code.
A model-driven approach to building AI agents in just a few lines of code.
Analyzes structured data and helps produce queries, insights or visualizations.
AI landscape generated with a freeform GAN based on highway images, and further processed with a style GAN using an original charcoal drawing.
Supports teaching, studying or skills practice with AI-guided learning tools.
Works with speech, voice, music or other audio using machine-learning models.
Creates, rewrites or summarizes written content with language models.
Small models, one shared log, and a clear view of how agents behave in motion.
Deep learning based facial detector for Python coming with facial landmarks.
A Collection of Awesome Generative AI Applications.