TabFM

TabFM

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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.

About

Tabular is an open table store from the creators of Apache Iceberg. Connect multiple computing engines and frameworks. Decrease query time and storage costs by up to 50%. Centralize enforcement of data access (RBAC) policies. Connect any query engine or framework, including Athena, BigQuery, Redshift, Snowflake, Databricks, Trino, Spark, and Python. Smart compaction, clustering, and other automated data services reduce storage costs and query times by up to 50%. Unify data access at the database or table. RBAC controls are simple to manage, consistently enforced, and easy to audit. Centralize your security down to the table. Tabular is easy to use plus it features high-powered ingestion, performance, and RBAC under the hood. Tabular gives you the flexibility to work with multiple “best of breed” compute engines based on their strengths. Assign privileges at the data warehouse database, table, or column level.

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

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

Audience

Developers in need of a data platform to connect compute engines and frameworks

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

Free
Free Version
Free Trial

Pricing

$100 per month
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

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

Company Information

Tabular
tabular.io

Alternatives

MLBox

MLBox

Axel ARONIO DE ROMBLAY

Alternatives

R2 SQL

R2 SQL

Cloudflare
Apache Iceberg

Apache Iceberg

Apache Software Foundation
T5

T5

Google

Categories

Categories

Integrations

AWS Identity and Access Management (IAM)
Alibaba Cloud
Amazon Athena
Amazon S3
Apache Iceberg
Apache Spark
Azure Databricks
Cloudera
Flink
Google Cloud BigQuery
Google Cloud Storage
HubSpot Customer Platform
MySQL
PostgreSQL
PuppyGraph
Python
SQL
Snowflake
Starburst Enterprise
Trino

Integrations

AWS Identity and Access Management (IAM)
Alibaba Cloud
Amazon Athena
Amazon S3
Apache Iceberg
Apache Spark
Azure Databricks
Cloudera
Flink
Google Cloud BigQuery
Google Cloud Storage
HubSpot Customer Platform
MySQL
PostgreSQL
PuppyGraph
Python
SQL
Snowflake
Starburst Enterprise
Trino
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Claim TabFM and update features and information
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