
Aquarium
Improve ML models by improving datasets they’re trained on
Aquarium launched on June 23, 2020 with 103 votes, #388 of 4,346 launches that month.
What it does
Machine learning models are only as good as the datasets they’re trained on, yet it’s extremely difficult to improve dataset quality. Aquarium uses deep learning to find problems in your model performance and edit your dataset to fix these problems.
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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