detr-doc-table-detection
detr-doc-table-detection is a model trained to detect both Bordered and Borderless tables in documents, based on facebook/detr-resnet-50.
Params
40 M
Context
1,024
Downloads 30d
198 K
Likes
64
Download history
daily snapshots · 75 days
▲ 26 K in the last 30 days (11.4%)
224 K197 K
Oct 12Oct 22Nov 1Nov 10
297 K197 K
Aug 28Sep 22Oct 17Nov 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 | 0.2 GB | 0.7 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
- DetrForObjectDetection
- Parameters
- 40 M
- Tensor type
- F32
- Context length
- 1,024
- Licence
- apache-2.0
- First seen on the Hub
- 2022-03-11
- Base model
- detr-resnet-50
- Training datasets
- MohamedExperio/ICDAR2019
- Added to our catalog
- 2026-08-28
Family
Base model and the most-downloaded derivatives in the catalog.
Compare with any object-detection model