Argilla is a collaboration tool for AI engineers and domain experts to build high-quality datasets
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Updated
Sep 9, 2024 - Python
Argilla is a collaboration tool for AI engineers and domain experts to build high-quality datasets
The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
skweak: A software toolkit for weak supervision applied to NLP tasks
Code associated to the article "Multi-annotator Deep Learning: A Probabilistic Framework for Classification"
A system for prompted weak supervision.
Code accompanying the TOP paper "Predicting the Demographics of Twitter Users with Programmatic Weak Supervision".
Pretrained segmenter models for Portuguese legislative text.
A system for quickly generating training data with weak supervision
Flippers is a weak supervision library for creating high quality labels using your domain kownledge and weak supervision sources.
An approach to curating naturally adversarial datasets.
[NeurIPS 2021] WRENCH: Weak supeRvision bENCHmark
Python Implementation of Weakly Supervised Clustering article
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.
Scaffolded Learning Regime for training maritime obstacle detection networks
Code for the KDD-2023 paper: Neural-Hidden-CRF: A Robust Weakly-Supervised Sequence Labeler
The source code used for paper "PIEClass: Weakly-Supervised Text Classification with Prompting and Noise-Robust Iterative Ensemble Training", published in EMNLP 2023.
Code for paper entitled "Learning to detect RFI in radio astronomy without seeing it"
Modeling task relationships with surrogate modeling
A collection of algorithms for detecting and handling label noise
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