TabFM

TabFM

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About

Computer vision and artificial intelligence (AI) helps train equipment to control the quality of products in manufacture, train robots for movement autonomous and safety, train cameras to control and analyze traffic on retail, recognize types and colors of cars, food in the fridge, or make a map or 3D model of space from video. Algorithms help to predict sales in your business, find the relationship between metrics, publications and grow, classify customers for prepare personal offers, interpret and visualize the data, extract most important from text and video. Data Mining, regression, classification, correlation and cluster analysis, decision trees, prediction models, graphs, neural networks. Text classification, understanding, summarization and auto-tagging, named-entity recognition, compare for text similarity, sentiment analysis, dialog and QA systems. Detection, segmentation, recognition, recovery and image/video generation.

About

TabFM is a zero-shot foundation model for tabular data, designed to simplify classification and regression workflows that traditionally require manual model training, hyperparameter tuning, and domain-specific feature engineering. Built specifically for tables, TabFM reframes tabular prediction as an in-context learning problem: instead of fitting a new supervised model to each dataset, it takes historical training examples and target testing rows together as one unified prompt, then interprets relationships between columns and rows at inference time. Because tables are two-dimensional and orderless, TabFM uses a hybrid architecture that combines alternating row and column attention, row compression, and a dedicated Transformer for in-context learning over compressed row embeddings. This design lets the model capture complex feature interactions and dependencies while keeping prediction computationally efficient for larger datasets.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

A solution to train equipment to control the quality of products in manufacture companies

Audience

Data scientists and analytics teams that need accurate tabular classification and regression without repetitive training, tuning, and feature-engineering work

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

PureMind
Founded: 2017
Russian Federation
puremind.tech/

Company Information

Google
Founded: 1998
United States
research.google/blog/introducing-tabfm-a-zero-shot-foundation-model-for-tabular-data/

Alternatives

Predictive Suite

Predictive Suite

Predictive Dynamix

Alternatives

MLBox

MLBox

Axel ARONIO DE ROMBLAY
T5

T5

Google
T5

T5

Google

Categories

Categories

Artificial Intelligence Features

Chatbot
For eCommerce
For Healthcare
For Sales
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)

Integrations

No info available.

Integrations

No info available.
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