facebook/detr-resnet-101
object-detection model by facebook
From the publisher
Model card & documentation
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DEtection TRansformer (DETR) model trained end-to-end on COCO 2017 object detection (118k annotated images). It was introduced in the paper End-to-End Object Detection with Transformers by Carion et al. and first released in this repository. Disclaimer: The team releasing DETR did not write a model card for this model so this model card has been written by the Hugging Face team. The DETR model is an encoder-decoder transformer with a convolutional backbone. Two heads are added on top of the decoder outputs in order to perform object detection: a linear layer for the class labels and a MLP (multi-layer perceptron) for the bounding boxes. The model uses so-called object queries to detect objects in an image. Each object query looks for a particular object in the image. For COCO, the number of object queries is set to 100. The model is trained using a "bipartite matching loss": one compares the…
Read the full model card ↗ · Preview checked 2026-10-28T02:00:48.866Z
Inside the original model card — Document outline
- DETR (End-to-End Object Detection) model with ResNet-101 backbone
- Model description
- Intended uses & limitations
- How to use
- Training data
- Training procedure
- Preprocessing
- Training
- Evaluation results
- BibTeX entry and citation info
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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
facebook/detr-resnet-101 is a object-detection model repository published by facebook 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)
- 20,967
- Cumulative likes
- 136
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 60,675,360
- Architecture
- DetrForObjectDetection
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2022-03-02T23:29:05.000Z
- Last modified
- 2023-12-14T17:21:17.000Z
Compatibility and lineage
Language coverage was not reported.
Base-model lineage was not included.
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
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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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