Version 0.14.0

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 and skorch.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

• the drop of Python 3.7 support - this version of Python has reached EOL and will not be supported anymore
• the NeptuneLogger now logs the skorch version thanks to @AleksanderWWW
• NeuralNetRegressor can now be fitted with 1-dimensional y, which is necessary in some specific circumstances (e.g. in conjunction with sklearn's BaggingRegressor, see #972); for this to work correctly, the output of the of the PyTorch module should also be 1-dimensional; the existing default, i.e. having y and y_pred be 2-dimensional, remains the recommended way of using NeuralNetRegressor

Full Changelog: v0.13.0...v0.14.0