snorkel VS argilla

Compare snorkel vs argilla and see what are their differences.

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snorkel argilla
5 14
5,500 1,988
0.5% 8.0%
5.5 8.6
about 1 month ago 2 days ago
Python Python
Apache License 2.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.


Posts with mentions or reviews of snorkel. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-03-03.


Posts with mentions or reviews of argilla. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-05-10.

What are some alternatives?

When comparing snorkel and argilla you can also consider the following projects:

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

spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python

weasel - Weakly Supervised End-to-End Learning (NeurIPS 2021)

label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format

cleanlab - The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

data-centric-ai - Resources for Data Centric AI

trankit - Trankit is a Light-Weight Transformer-based Python Toolkit for Multilingual Natural Language Processing

doccano - Open source annotation tool for machine learning practitioners.

dalle-flow - 🌊 A Human-in-the-Loop workflow for creating HD images from text

dataqa - Labelling platform for text using weak supervision.

caer - High-performance Vision library in Python. Scale your research, not boilerplate.