jrzaurin/pytorch-widedeep

Health v2 · maintenance only

Adoption not part of the score

1416 stars · 197 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A PyTorch library for multimodal deep learning that combines tabular data with text and images using Wide and Deep model architectures. It provides flexible components for building deep learning models on mixed-modality datasets.

Use cases

• train deep learning models on tabular data with pytorch
• combine tabular features with text and images in one model
• build wide and deep recommendation models
• use transformers for text columns alongside tabular data
• benchmark tabular deep learning against lightgbm
• multimodal classification with mixed data types

When to choose

• your dataset mixes tabular, text, and image inputs
• you want Wide and Deep architectures in PyTorch
• you need flexible deep tabular modeling with pretrained text/image encoders

When to avoid

• you only need gradient-boosted trees like LightGBM/XGBoost
• you need a general-purpose deep learning framework rather than tabular-focused tooling
• you work outside Python/PyTorch

Facets

library · maturity active

machine-learning deep-learning nlp image-processing data-science machine-learning deep-learning data-science computer-vision python cross-platform pytorch tabular-data wide-and-deep multimodal transformers model-hub natural-language-processing

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