Framework for distributed hyperparameter optimization.
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A very simple wrapper for convenient hyperparameter optimization.
Distributed Asynchronous Hyperparameter Optimization in Python.
Toolset for black-box hyperparameter optimisation.
Easy-to-use, scalable hyperparameter optimization framework.
Respan unifies LLM observability, evals, prompt optimization, and an AI gateway so teams can ship reliable AI applications.
Build better AI systems with evals, RAG, agents, synthetic data, fine-tuning, and prompt optimization. Free app + open-source library.
LLM Ops platform with Analytics, Monitoring, Evaluations and an LLM Optimization Studio powered by DSPy.
A Clojure library of optimisation and control theory tools and convenience functions based on Neanderthal.
Ncnn is a high-performance neural network inference framework optimized for the mobile platform.
Open-source module for running AI workloads on Kubernetes in an optimized way.
A Python-inspired implementation of the Optimum-Path Forest classifier.
An optimization library for Torch. SGD, Adagrad, Conjugate-Gradient, LBFGS, RProp and more.
Google TPU optimizations for transformers models.
Cleansing, pre-processing, feature engineering, exploratory data analysis and easy ML with PySpark backend.
Optuna is an automatic hyperparameter optimization software framework, particularly designed for machine learning.
Python-based meta-heuristic optimization techniques.
EPUB to audiobook converter, optimized for Audiobookshelf.
"Optimize Your Prompts to Perfection".
A general-purpose network embedding framework: pair-wise representations optimization Network Edit.
File Parser optimised for LLM Ingestion with no loss. Parse PDFs, Docx, PPTx in a format that is ideal for LLMs.
Bayesian optimization in high-dimensions via random embedding.
Robust Bayesian Optimization framework.
Simple and efficient library to minimize expensive and noisy black-box functions.