detr-resnet-50
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.
Params
40 M
Context
1,024
Downloads 30d
637 K
Likes
975
Download history
daily snapshots · 55 days
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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
- 2022-03-02
- Training datasets
- coco
- Added to our catalog
- 2026-07-28
Family
Base model and the most-downloaded derivatives in the catalog.
Compare with any object-detection model