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Prodigy
Prodigy is an annotation tool for creating training and evaluation data for machine learning models, error analysis, data inspection & cleaning. W&B Tables allow you to log, visualize, analyze, and share datasets (and more!) inside W&B.
The W&B integration with Prodigy adds simple and easy-to-use functionality to upload your Prodigy-annotated dataset directly to W&B for use with Tables.
Run a few lines of code, like these:
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import wandb
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from wandb.integration.prodigy import upload_dataset
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with wandb.init(project="prodigy"):
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upload_dataset("news_headlines_ner")
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and get visual, interactive, shareable tables like this one:

Quickstart

Use wandb.integration.prodigy.upload_dataset to upload your annotated prodigy dataset directly from the local Prodigy database to W&B in our Table format. For more information on Prodigy, including installation & setup, please refer to the Prodigy documentation.
W&B will automatically try to convert images and named entity fields to wandb.Image and wandb.Htmlrespectively. Extra columns may be added to the resulting table to include these visualizations.

Read through a detailed example

This W&B Report demonstrates visualizations generated using the W&B Prodigy integration:
Visualizing Prodigy Datasets Using W&B Tables
W&B

Also using spaCy?

W&B also has an integration with spaCy, see the docs here.
Last modified 2mo ago