TabFM

TabFM

Google
+
+

Related Products

  • AthenaHQ
    36 Ratings
    Visit Website
  • Evertune
    1 Rating
    Visit Website
  • ONLYOFFICE Docs
    715 Ratings
    Visit Website
  • Passwork
    126 Ratings
    Visit Website
  • Criminal IP ASM
    20 Ratings
    Visit Website
  • VisitUs Reception
    86 Ratings
    Visit Website
  • Setplex
    10 Ratings
    Visit Website
  • Nexo
    18,609 Ratings
    Visit Website
  • ThriveSparrow
    43 Ratings
    Visit Website
  • Podium
    2,128 Ratings

About

Introducing DeepSeek-V3.2-Exp, our latest experimental model built on V3.1-Terminus, debuting DeepSeek Sparse Attention (DSA) for faster and more efficient inference and training on long contexts. DSA enables fine-grained sparse attention with minimal loss in output quality, boosting performance for long-context tasks while reducing compute costs. Benchmarks indicate that V3.2-Exp performs on par with V3.1-Terminus despite these efficiency gains. The model is now live across app, web, and API. Alongside this, the DeepSeek API prices have been cut by over 50% immediately to make access more affordable. For a transitional period, users can still access V3.1-Terminus via a temporary API endpoint until October 15, 2025. DeepSeek welcomes feedback on DSA via its feedback portal. In conjunction with the release, DeepSeek-V3.2-Exp has been open-sourced: the model weights and supporting technology (including key GPU kernels in TileLang and CUDA) are available on Hugging Face.

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

Researchers and AI engineers looking for a solution providing a model that performs well on long-context tasks with reduced compute cost

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

Free
Open source
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

DeepSeek
Founded: 2023
China
deepseek.com

Company Information

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

Alternatives

Alternatives

Evo 2

Evo 2

Arc Institute
DeepSeek-V3.2

DeepSeek-V3.2

DeepSeek
MiniMax M2

MiniMax M2

MiniMax
DeepSeek-V2

DeepSeek-V2

DeepSeek
MLBox

MLBox

Axel ARONIO DE ROMBLAY

Categories

Categories

Integrations

DeepSeek
Hugging Face

Integrations

DeepSeek
Hugging Face
Claim DeepSeek-V3.2-Exp and update features and information
Claim DeepSeek-V3.2-Exp and update features and information
Claim TabFM and update features and information
Claim TabFM and update features and information