---
license: other
license_name: bsd-3-clause-openmdw-1.1-apache-2.0
license_link: LICENSE.md
library_name: onnx
base_model:
  - jingang/TabICL
  - nvidia/Kumo-Tabular
  - nvidia/Kumo-Relational
  - amazon/chronos-2
  - autogluon/chronos-2-small
  - nvidia/Kumo-Anomaly
base_model_relation: quantized
tags:
  - onnx
  - onnxruntime-web
  - webgpu
  - tabular-classification
  - tabular-regression
  - time-series-forecasting
  - anomaly-detection
  - tabular-foundation-model
  - relational-foundation-model
  - in-context-learning
---

# ONNX models for Tabular Data Workbench

Unofficial ONNX conversions of six open foundation models, made for Tabular
Data Workbench, a browser app that runs them with onnxruntime-web on WebGPU
or WebAssembly. The weights are the upstream authors': the `fp32` files hold
them unchanged, and the `f16w` files store the larger ones as float16. The
upstream authors have not reviewed or endorsed these conversions.

| folder | models | upstream | licence | size (fp32 + f16w) |
| --- | --- | --- | --- | --- |
| [`tabicl/`](tabicl/README.md) | TabICLv2 classifier and regressor | [jingang/TabICL](https://huggingface.co/jingang/TabICL) (Soda team, Inria) | BSD-3-Clause | 339 MB |
| [`kumo/`](kumo/README.md) | Kumo Tabular small, medium and large, classifier and regressor | [nvidia/Kumo-Tabular](https://huggingface.co/nvidia/Kumo-Tabular) (NVIDIA) | OpenMDW-1.1 | 1.2 GB (f16w only) |
| [`rfm/`](rfm/README.md) | Kumo Relational classifier and regressor | [nvidia/Kumo-Relational](https://huggingface.co/nvidia/Kumo-Relational) (NVIDIA) | OpenMDW-1.1 | 367 MB |
| [`tsfm/`](tsfm/README.md) | Chronos-2, Chronos-2 small, Kumo-Anomaly | [amazon/chronos-2](https://huggingface.co/amazon/chronos-2), [autogluon/chronos-2-small](https://huggingface.co/autogluon/chronos-2-small) (Amazon), [nvidia/Kumo-Anomaly](https://huggingface.co/nvidia/Kumo-Anomaly) (NVIDIA) | Apache-2.0 | 901 MB |

Each folder holds a `manifest.json` (every file's size and sha256, the
graphs' inputs and outputs, model settings and parity figures), the licence
and notice files for its models, and each graph in two variants. `fp32` has
the weights as released. `f16w` stores every float32 weight of 1,024 or more
elements as float16 and casts it back to float32 on load, which halves the
download and keeps compute in float32. `kumo/` has the `f16w` variant only.
The README in each folder describes its graphs, how they were made and how
closely they match the reference implementation.

The graphs are the networks only. Preprocessing, ensembling, sampling and
decoding stay outside them, as in the reference packages, and the app
implements them in TypeScript. The `models/` folder of Tabular Data Workbench
has the export scripts and the numpy references for these steps.

## Use in the app

The app reads `<base>/<folder>/manifest.json` and the files it lists, and
checks each file's sha256 before caching it. To serve the models from this
repository, build the app with the base URL pinned to a commit:

```sh
VITE_MODELS_BASE_URL=https://huggingface.co/ScriptSmith/tabular-data-workbench-onnx/resolve/<commit>/ pnpm build
```

## How they were made

The scripts are in the `models/` folder of Tabular Data Workbench, one uv
workspace. They use PyTorch 2.14 on CPU and the `torch.onnx` dynamo exporter
at opset 18 (opset 20 for `kumo/`), and check the graphs with onnxruntime
1.30:

```sh
# from the root of the Tabular Data Workbench source
(cd models/tabicl && uv run export.py)
(cd models/kumo && uv run export.py)
node models/rfm/dump_shop.mjs   # once: the sample tables rfm's checks run on
(cd models/rfm && uv run export.py)
(cd models/tsfm && uv run export_chronos2.py && uv run export_kumo.py)
```

Every export checks its graphs against the reference package (tabicl,
structured-data-models, chronos-forecasting) before it writes the manifest.
The exports also remove the exporter's node metadata and doc strings, which
hold stack traces with the paths of the machine that ran them.

## Licences

The folders are under different licences, listed in [`LICENSE.md`](LICENSE.md):

- `tabicl/`: BSD-3-Clause, Copyright (c) 2025, Soda team @ Inria (`tabicl/LICENSE`).
- `kumo/`: OpenMDW-1.1, Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES
  (`kumo/LICENSE`), with a notice of origin and changes (`kumo/NOTICE`, which
  also carries the BSD-3-Clause notice for the TabICLv2-derived code) and the
  Apache-2.0 licence of structured-data-models (`kumo/LICENSE.structured-data-models`).
- `rfm/`: OpenMDW-1.1, Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES
  (`rfm/LICENSE`), with NVIDIA's notice for the TabICLv2 weights it was
  fine-tuned from (`rfm/THIRD-PARTY-NOTICES.txt`, BSD-3-Clause) and the
  Apache-2.0 licence of structured-data-models (`rfm/LICENSE.structured-data-models`).
- `tsfm/`: Apache-2.0 (`tsfm/LICENSE`), with Amazon's and NVIDIA's notices
  and a statement of the changes (`tsfm/NOTICE`), and DPM-Solver's MIT
  licence (`tsfm/THIRD-PARTY-NOTICES.txt`).

Keep each folder's licence and notice files with its ONNX files when
redistributing them.