table-transformer-structure-recognition
Table Transformer (DETR) model trained on PubTables1M. It was introduced in the paper PubTables-1M: Towards Comprehensive Table Extraction From Unstructured Documents by Smock et al. and first released in this repository.
Params
30 M
Context
1,024
Downloads 30d
1.3 M
Likes
245
Download history
daily snapshots · 106 days
▲ 89 K in the last 30 days (7.2%)
1.4 M1.2 M
Oct 12Oct 22Nov 1Nov 10
1.4 M1.1 M
Aug 13Sep 12Oct 12Nov 10
1.6 M1.1 M
Jul 28Sep 1Oct 6Nov 10
Can you run it?
Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.
| File | Quant | Size | Est. VRAM | Verdict on RTX 4090 · 24 GB |
|---|---|---|---|---|
| model.safetensors | f32 | 0.1 GB | 0.6 GB | ✅ Runs comfortably |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Specifications
- Architecture
- TableTransformerForObjectDetection
- Parameters
- 30 M
- Tensor type
- F32
- Context length
- 1,024
- Licence
- mit
- First seen on the Hub
- 2022-10-14
- Training datasets
- undisclosed
- Added to our catalog
- 2026-07-28
Compare with any object-detection model