snorkel-team/snorkel

Health v2 · maintenance only

Adoption not part of the score

6001 stars · 858 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Snorkel is a Python library for programmatically building and managing training data using weak supervision, letting users write labeling functions instead of hand-labeling data. It also supports data augmentation and data slicing, and originated as a Stanford research project.

Use cases

• generate training data without manual labeling
• write labeling functions for weak supervision
• programmatically label a large dataset
• augment training data for machine learning
• create data slices to evaluate model performance
• denoise noisy labels from multiple labeling sources

When to choose

• you need to label large datasets quickly without hand-annotation
• you have domain heuristics that can be encoded as labeling functions
• you want research-backed weak supervision modeling in Python

When to avoid

• you need an end-to-end commercial platform with a UI (consider Snorkel Flow)
• you expect active feature development, as the team has shifted focus to Snorkel Flow
• you need fully automated labeling with no heuristic input

Facets

library · maturity maintenance

machine-learning data-science etl machine-learning data-science artificial-intelligence python cross-platform weak-supervision data-labeling training-data data-augmentation data-slicing labeling-functions

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