sklearn.utils are meant to be used internally within the scikit-learn package. They are not guaranteed to be stable between versions of scikit-learn. So depending on this submodule may limit cleanlab compatibility across sklearn versions.
Would not be too much work to replace the few cleanlab functions currently being
The default RubrixLogHTTPMiddlewarerecord mapper for token classification expect a structured including a text field for inputs. This could make prediction model inputs a bit cumbersome. Default mapper could accepts also flat strings as inputs:
deftoken_classification_mapper(inputs, outputs):
i
This is the code for our paper `Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach' (In Proc. of NAACL-HLT 2021).
A PyTorch-based open-source framework that provides methods for improving the weakly annotated data and allows researchers to efficiently develop and compare their own methods.
sklearn.utils are meant to be used internally within the scikit-learn package. They are not guaranteed to be stable between versions of scikit-learn. So depending on this submodule may limit cleanlab compatibility across sklearn versions.
Would not be too much work to replace the few cleanlab functions currently being