Generate Keras models from a description.https://twitter.com/mattshumer_/status/1287125015528341506 …
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1. Use a supervised text model to go from description to structured representation, trained on a specialized dataset 2. Use a hard coded algorithm to generate Keras code from the structured representation (ensures code reliability)
Also, the right input for autoML is not a model description, but a task description and a dataset That said, this app demonstrates the power of GPT-3 for quick prototyping!
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This could be one interesting direction for AutoML, getting from a non-expert user a description of the problem/dataset and some constraints, but rather than producing not model directly, output a description of the search space that then an AutoML strategy would optimize over.
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That was the exact approach I took with my AutoML project I released last year. (unfortunately I haven't had the time to improve it)https://github.com/minimaxir/automl-gs …
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At least it chose keras !
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