Weak Supervision Python Packages

snorkel

A system for quickly generating training data with weak supervision

cleanlab

Cleanlab's open-source library is the standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

rubrix

Argilla is a collaboration tool for AI engineers and domain experts to build high-quality datasets

argilla-server

Open-source tool for exploring, labeling, and monitoring data for NLP projects.

spacy-partial-tagger

A simple library for training named entity recognition model from partially annotated data

skweak

skweak: A software toolkit for weak supervision applied to NLP tasks

finest

FineST: Fine-grained Spatial Transcriptomic

auto-annotate

Labeling is boring. Use this tool to speed up your next object detection project!

example-package-elisno

The standard package for data-centric AI, machine learning with label errors, and automatically finding and fixing dataset issues in Python.

decile-spear

SPEAR: Programmatically label and build training data quickly.

argilla-v1

Open-source tool for exploring, labeling, and monitoring data for NLP projects.

scikit-clean

A collection of algorithms for detecting and handling label noise

flippers

`flippers` is a weak supervision library for creating high quality labels using domain kownledge and heuristics.

ws-benchmark

a benchmark for weak supervision

knodle

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.

hyperlm

A hyper label model to aggregate multiple weak labels in a single forward pass

snorkel-ie

a lightweight framework for developing structured information extraction applications