TabFM

TabFM

Google
+
+

Related Products

  • Innoslate
    93 Ratings
    Visit Website
  • Azore CFD
    26 Ratings
    Visit Website
  • Concord
    237 Ratings
    Visit Website
  • LTX
    182 Ratings
    Visit Website
  • Gemini Enterprise Agent Platform
    999 Ratings
    Visit Website
  • IONOS Cloud GPU Servers
    45,199 Ratings
    Visit Website
  • Macaw AMS
    8 Ratings
    Visit Website
  • SMS Storetraffic
    127 Ratings
    Visit Website
  • CompUp
    66 Ratings
    Visit Website
  • Odoo
    1,714 Ratings
    Visit Website

About

ChemSep is a column simulator designed for distillation, absorption, and extraction operations, combining classic equilibrium stage and nonequilibrium (rate-based) models within an intuitive interface. The software includes a comprehensive library of capacity and mass transfer performance parameters for trays and packings, facilitating accurate modeling of actual column performance. ChemSep's design mode allows for automatic simulation and column diameter determination based on specified fractions of the flood, integrating vendor design methods and pressure drop models for trayed and packed columns. The program supports various column configurations and specifications, enabling users to solve separation problems efficiently. ChemSep operates as a standalone application or can be embedded within any CAPE-OPEN compliant flowsheeting package, utilizing their thermodynamic and physical property data.

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 Supported
Mac Supported
Linux Not Supported
Cloud Not Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

Students seeking a tool to learn and practice modeling separation processes such as distillation, absorption, and extraction

Audience

Data scientists and machine learning teams seeking to perform zero-shot classification and regression on tabular data without task-specific training

Support

Phone Support Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Not Supported

API

Offers API Not Supported

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Pricing

Free
Free Version Supported
Free Trial Not Supported

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 Supported
Webinars Not Supported
Live Online Not Supported
In Person Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

ChemSep
Netherlands
www.chemsep.org

Company Information

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

Alternatives

Alternatives

TabPFN-3.5

TabPFN-3.5

Prior Labs
SuperPro Designer

SuperPro Designer

Intelligen
Evo 2

Evo 2

Arc Institute
ChemOffice

ChemOffice

PerkinElmer Informatics
ChemDraw

ChemDraw

PerkinElmer
ChemStat

ChemStat

Starpoint Software

Categories

Simulation Supported

Categories

AI Models Supported
Foundation Models Supported

Integrations

No info available.

Integrations

No info available.
Claim ChemSep and update features and information
Claim ChemSep and update features and information
Claim TabFM and update features and information
Claim TabFM and update features and information