Prodigy

Integrate W&B with Prodigy to track annotation workflows, log training metrics, and manage labeled datasets.

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:

import wandb
from wandb.integration.prodigy import upload_dataset

with wandb.init(project="prodigy"):
    upload_dataset("news_headlines_ner")

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

Explore the Visualizing Prodigy Datasets Using W&B Tables for example visualizations generated with W&B Prodigy integration.