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Doccano is a collaborative labeling platform and text annotation tool designed to create training data for machine learning. It provides a specialized interface for performing sequence labeling and text classification on natural language datasets. The system functions as a supervised learning dataset manager, allowing multiple users to coordinate within a shared workspace to label datasets for natural language processing tasks. It supports the preparation of raw text data for model training by converting unstructured documents into structured labeled examples. The platform includes capabilit
Welcome to NPLM (Noisy Partial Label Model), a programmatic weak supervision system that supports (partial) labeling functions with supervision granuarity ranging from class to a set of classes.
The data scientist's open-source choice to scale, assess and maintain natural language data. Treat training data like a software artifact.
This is a PyTorch-Lightning-based framework, based on our End-to-End Weak Supervision paper (NeurIPS 2021), that allows you to train your favorite neural network for weakly-supervised classification 1
The main features of dataqa/nlp-labelling are: Text Annotation Tools.
Open-source alternatives to dataqa/nlp-labelling include: chakki-works/doccano — Doccano is a collaborative labeling platform and text annotation tool designed to create training data for machine… davidjurgens/potato — potato: the portable annotation tool. code-kern-ai/refinery — The data scientist's open-source choice to scale, assess and maintain natural language data. Treat training data like… cogcomp/talen — -->. batsresearch/nplm — Welcome to NPLM (Noisy Partial Label Model), a programmatic weak supervision system that supports (partial) labeling… autonlab/weasel — This is a PyTorch-Lightning-based framework, based on our End-to-End Weak Supervision paper (NeurIPS 2021), that…