tabularfamily
TabNet
Deep learning model for tabular data that uses sequential attention to choose which features to reason from at each step, which makes its decisions interpretable. Paper by Arik and Pfister (2019).
Levelfamily
Classtabular
Parametersnot in the notes
Contextnot in the notes
Released20 Aug 2019
Opennessopen source
Runs onnot in the notes
Statusactive
Identity
- Developer
- not in the notes
- Family
- not in the notes
- Released
- 20 Aug 2019 sourcesannouncement page
- Weights published
- –
- Record checked
- 12 Oct 2026
Where this comes from
Developer and dates from the research notes. Release date is the vendor's public announcement; weights date is when open weights were published.
Architecture and Size
- Architecture
- dense transformer Sequential attention that selects features at each decision step
- Total parameters
- – sources
- Active parameters
- –
- Checkpoint parameters
- –
- Context length
- not in the notes
- Input
- table
- Output
- table
Where this comes from
Parameter counts as the developer states them. Where the checkpoint holds a different total, both are shown (register A16).
Openness and Access
- Openness
- open source
- Licence
- MIT License sources
- Access routes
- not in the notes
Where this comes from
The licence file governs over registry tags and aggregator labels.
Deployment
- Runs on
- not in the notes
- Footprint
- Licence is that of the dreamquark-ai/tabnet PyTorch implementation (MIT); the paper itself carries no licence.
- Runtimes
- not in the notes
Where this comes from
Deployment tiers and runtimes as named in the notes. Footprint is the notes' figure, not a measurement by AURION.
Indonesia
- Indonesian support
- not stated
- Regional languages
- not in the notes
- Jakarta hosting
- unknown
- Languages
- not in the notes
Where this comes from
Indonesia fields are carried on every model; unknown is an allowed value.
Benchmark Results
The notes record no benchmark result for this model.
Lineage
The notes record no lineage for this model.
Industry Use Cases
No industry use case links this model.
Links
Developersnone recorded
ModelTabNettabular
Use CasesOil Palm Yield PredictionAgricultureRoute OptimisationRetail and LogisticsUse cases of models in the same R&D topic; none is recorded for this model itself.
Who Runs It
PT Astra Agro Lestari TbkIn production, 21 Sep 2026
J&T Express IndonesiaIn production, 26 Aug 2026Unnamed Indonesian estate (15,000 to 17,000 ha)In production, 2024Deployments of these use cases; none names this model.
PT Astra Agro Lestari TbkIn production, 21 Sep 2026J&T Express IndonesiaIn production, 26 Aug 2026Unnamed Indonesian estate (15,000 to 17,000 ha)In production, 2024Deployments of these use cases; none names this model.Sources
- arxiv.org/abs/1908.07442 https://arxiv.org/abs/1908.07442
- github.com/dreamquark-ai/tabnet https://github.com/dreamquark-ai/tabnet
- github.com/manujosephv/pytorch_tabular https://github.com/manujosephv/pytorch_tabular
- modelzoo.co/model/tabnet https://modelzoo.co/model/tabnet
To cite this page: Project AURION, AI Use-Cases Research & Innovation, "TabNet", https://aurion.semai.id/models/tabnet/, records of October 2026.