Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Prepare release 0.14.0 #985

Merged
merged 1 commit into from
Jun 26, 2023
Merged

Prepare release 0.14.0 #985

merged 1 commit into from
Jun 26, 2023

Conversation

ottonemo
Copy link
Member

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 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 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. having y and y_pred be 2-dimensional, remains the recommended way of using NeuralNetRegressor

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

@BenjaminBossan BenjaminBossan merged commit 4c5cfda into master Jun 26, 2023
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

Successfully merging this pull request may close these issues.

2 participants