Adaption

Founded by Sara Hooker in 2025

Train custom machine learning models and improve datasets with continuous learning capabilities

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You can use Adaption to train custom machine learning models and prepare high-quality training datasets across hundreds of languages. The service lets you connect data sources like HuggingFace or direct file uploads, repair existing datasets, or generate synthetic training data when none exists. Its AutoScientist feature automatically sets up experiments, tests training recipes, and refines models for your specific domain tasks. You retain complete ownership of your trained weights and data pipelines while keeping models up to date with new information over time.

What Adaption does

Connect data sources via Hugging Face or direct file uploadRun automated training experiments with AutoScientistSynthesize new training data for specific domain gapsClean and filter existing multi-language text datasetsExport trained model weights to internal serving infrastructureMonitor model adaptation performance across specialized tasksAutoScientist automates experimental model training recipesCleans and expands datasets across 242 regional languagesGenerates synthetic training data for domain-specific tasksDirect integration with Hugging Face and Kaggle repositoriesContinuous learning updates models post-deployment at inferenceDirect export and ownership of trained model weights