skillfed

autogluon.text

AutoML for Image, Text, and Tabular Data

autogluon-text v0.6.2 84.6K downloads/30d#13,983 on PyPI10,596
Permissive license Apache-2.0 Active released

What it is and what it does

autogluon.text is a specialized AutoML package for text classification and prediction tasks. It wraps AutoGluon's text prediction capabilities, allowing you to train deep learning models on text data with just a few lines of code—no manual feature engineering or hyperparameter tuning required. The package handles model selection, training, and evaluation automatically, targeting use cases where you have labeled text data and want a production-ready predictor quickly.

The package depends on autogluon.multimodal, which provides the underlying neural network infrastructure. It's designed for developers and data scientists who want to avoid the complexity of building text models from scratch but need reasonable accuracy without extensive ML expertise. The API mirrors AutoGluon's other predictors (TabularPredictor, ImagePredictor), making it familiar if you've used other AutoGluon modules.

Use it for:

  • Train a text classifier on customer feedback or support tickets to automatically categorize incoming messages.
  • Build a sentiment analysis model on labeled reviews without writing custom neural network code.
  • Quickly prototype a text-based prediction model for a Kaggle competition or proof-of-concept.
  • Deploy a production text classifier that automatically selects and tunes models for your specific dataset.
  • Combine text predictions with other data types using AutoGluon's multimodal capabilities.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Automates machine learning for text data, training and deploying high-accuracy models with minimal code through AutoGluon's text prediction interface.

Yes, if you need to train text models quickly without deep ML expertise and can work within Python 3.7–3.9. The low install friction, active maintenance, permissive license, and zero known vulnerabilities make it a solid choice for prototyping and production use. No, if you require the latest Python versions or need fine-grained control over model architecture—use lower-level libraries like transformers or PyTorch instead.

Install

autogluon-text on PyPI

pip

pip install autogluon-text

uv

uv add autogluon-text

poetry

poetry add autogluon-text

Installing autogluon.text

Before you install

Low install friction with a single runtime dependency (autogluon.multimodal). The package is actively maintained with recent commits and has been in active development since its first release in 2020.

License in practice

Licensed under Apache-2.0 (permissive), allowing free use, modification, and distribution with minimal restrictions—suitable for both open-source and commercial projects.

Quickstart

pip install autogluon.text

from autogluon.text import TextPredictor
predictor = TextPredictor(label='class').fit(train_data, time_limit=120)
leaderboard = predictor.leaderboard(test_data)

Requires Python 3.7–3.9 (capped below current versions); check your environment before installing.

Verify before relying

  • Whether autogluon.multimodal's own dependencies introduce significant additional install friction or system requirements.
  • Current state of model download sizes and memory requirements for typical text prediction tasks.
  • Performance characteristics and training time for different text dataset sizes.

Package facts

License Apache-2.0 (permissive)
Python support capped below the current Python release (>=3.7, <3.10)
Install friction low — pure-Python wheel
Runtime dependencies 1 — autogluon.multimodal
Maintenance actively maintained — 1,311 days since the last release
Last repo commit
First released
Downloads 84,617/month — #13,983 on PyPI (30-day window, as of 2026-08-14)
Known vulnerabilities none known (OSV.dev, checked 2026-08-14)

Evidence: autogluon.text-0.6.2-py3-none-any.whl

Development Status :: 4 - BetaIntended Audience :: Customer ServiceIntended Audience :: DevelopersIntended Audience :: EducationIntended Audience :: Financial and Insurance IndustryIntended Audience :: Healthcare IndustryIntended Audience :: Science/ResearchIntended Audience :: Telecommunications IndustryLicense :: OSI Approved :: Apache Software LicenseOperating System :: MacOSOperating System :: Microsoft :: WindowsOperating System :: POSIXOperating System :: UnixProgramming Language :: Python :: 3Programming Language :: Python :: 3.7Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Topic :: Scientific/Engineering :: Artificial IntelligenceTopic :: Scientific/Engineering :: Image RecognitionTopic :: Scientific/Engineering :: Information AnalysisTopic :: Software Development

Tags

automl text classificationautomated text predictiontext nlp machine learningdeep learning text modelstext data automlneural text classificationautomated nlp training
automltext-classificationnlp

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Further reading