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Preparation of the 0.14.0 release.
I think that we can also include #974 once the pipelines succeed.
Here's a suggestion for the release text:
This release offers a new interface for scikit-learn to do zero-shot and few-shot classification using open source large language models (Jump right into the example notebook).
skorch.llm.ZeroShotClassifier
andskorch.llm.FewShotClassifier
allow the user to do classification using open-source language models that are compatible with the huggingface generation interface. This allows you to do all sort of interesting things in your pipelines. From simply plugging a LLM into your classification pipeline to get preliminary results quickly, to using these classifiers to generate training data candidates for downstream models. This is a first draft of the interface, therefore it is not unlikely that the interface will change a bit in the future, so please, let us know about any potential issues you have.Other items of this release are
NeptuneLogger
now logs the skorch version thanks to @AleksanderWWWNeuralNetRegressor
can now be fitted with 1-dimensionaly
, which is necessary in some specific circumstances (e.g. in conjunction with sklearn'sBaggingRegressor
, see sklearn.ensemble.BaggingRegressor() #972); for this to work correctly, the output of the of the PyTorch module should also be 1-dimensional; the existing default, i.e. havingy
andy_pred
be 2-dimensional, remains the recommended way of usingNeuralNetRegressor
Full Changelog: v0.13.0...v0.14.0