jianzhnie/MultimodalTookit

Incorporate Image, Text and Tabular Data with HuggingFace Transformers

21
/ 100
Experimental

This toolkit helps you make better predictions or classifications using a mix of data types, like customer reviews (text), product details (numbers), and images. It takes these different kinds of information, processes them, and then outputs a prediction or a category, such as whether a customer will recommend a product or the likelihood of pet adoption. It's for data scientists and machine learning engineers who need to build robust models from diverse datasets.

No commits in the last 6 months.

Use this if you need to build a machine learning model that predicts an outcome or classifies data, and your input data includes a combination of text, images, and traditional numerical or categorical information.

Not ideal if your dataset only contains a single data type (e.g., only text or only tabular numbers) or if you are not working with prediction or classification tasks.

predictive-modeling multi-modal-data-analysis classification regression data-science
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 0 / 25

How are scores calculated?

Stars

12

Forks

Language

Python

License

Apache-2.0

Last pushed

Mar 01, 2022

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/transformers/jianzhnie/MultimodalTookit"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.