gilad-rubin/hypster
HyPSTER - Configuration Framework for Optimizing AI & AI Systems
Provides hierarchical, type-safe configuration management with first-class hyperparameter optimization via Optuna integration. Uses a define-by-run API where configuration functions declare parameters (selects, floats, ints) that can be explored, validated, and instantiated with value overrides. Targets ML/AI workflows requiring both flexible nested configurations and automated hyperparameter search capabilities.
Available on PyPI.
Stars
57
Forks
2
Language
Python
License
MIT
Category
Last pushed
Jan 29, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/generative-ai/gilad-rubin/hypster"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related tools
BloombergGraphics/2024-openai-gpt-hiring-racial-discrimination
Data and materials to reproduce Bloomberg's investigation into racial and gender bias in OpenAI's GPT
risabhmishra/algotrading-sentimentanalysis-genai
Algorithmic Trading with Sentiment Analysis using GenAI
MoAshour93/ConstructionAI
This repository contains projects developed to showcase how to apply Generative AI and...
galafis/python-nlp-sentiment-analysis
Data Science project - python-nlp-sentiment-analysis
galafis/Natural-Language-Processing-Suite
Comprehensive NLP toolkit with text classification, named entity recognition, sentiment...