TahaDouaji/detr-doc-table-detection
object-detection model by TahaDouaji
From the publisher
Model card & documentation
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detr-doc-table-detection is a model trained to detect both Bordered and Borderless tables in documents, based on facebook/detr-resnet-50. This model can be used for the task of object detection. The model should not be used to intentionally create hostile or alienating environments for people. Significant research has explored bias and fairness issues with language models (see, e.g., Sheng et al. (2021) and Bender et al. (2021)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups. Users (both direct and downstream) should be made aware of…
Read the full model card ↗ · Preview checked 2026-10-31T19:33:26.134Z
Inside the original model card — Document outline
- Model Card for detr-doc-table-detection
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- Direct Use
- Out-of-Scope Use
- Bias, Risks, and Limitations
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Documentation belongs to its respective authors. Reported project/model license: apache-2.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
Model overview
TahaDouaji/detr-doc-table-detection is a object-detection model repository published by TahaDouaji on Hugging Face. The source reports the transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- object-detection
- Library
- transformers
- Recent downloads (30 days)
- 173,097
- Cumulative likes
- 64
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 41,608,135
- Architecture
- DetrForObjectDetection
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2022-03-11T15:55:14.000Z
- Last modified
- 2025-11-10T05:52:21.000Z
Compatibility and lineage
Language coverage was not reported.
Reported base models: facebook/detr-resnet-50
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
Check license terms and access requirements first. Review the model card’s documented loading instructions, evaluations and safety limitations. Benchmark scores are not imported by this directory, and popularity is not an accuracy ranking.
No model weights are downloaded or executed by AltAPIs. Never enable remote model code without reviewing it.
Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-11-01T06:54:34.007Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.
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