# dab-detr-resnet-50 by IDEA-Research: Open-Weight Model Source: https://savrn.com/models/dab-detr-resnet-50 Markdown alternate of the page above; the site index is https://savrn.com/llms.txt --- ## Runs On What it takes to serve dab-detr-resnet-50 (44M parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them. | Precision | Weights | Memory needed | Cheapest setup | Per hour | Also fits | | --- | --- | --- | --- | --- | --- | | 16-bit | 0.1 GB | 0.1 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 | | 8-bit | 0.0 GB | 0.1 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 | | 4-bit | 0.0 GB | 0.0 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 | Memory is the weights at that precision plus 20% for the runtime and a short context; a long context needs more. Prices are the lowest on-demand hourly rates in the [SAVRN Index](https://savrn.com/ai-index/pricing/gpus), read Oct 25, 2026. [dab-detr-resnet-50 on every accelerator the SAVRN Index prices, at every precision](https://savrn.com/models/dab-detr-resnet-50/gpus) ## Model Card By IDEA-Research, published under apache-2.0, revision d8e2856ee1f7. ### Model Card for Model ID ### Table of Contents 1. Model Details 2. Model Sources 3. How to Get Started with the Model 4. Training Details 5. Evaluation 6. Model Architecture and Objective 7. Citation ### Model Details [Read the full model card (861 words)](https://savrn.com/models/dab-detr-resnet-50/card) ## Configuration Architecture DabDetrForObjectDetection Layers 6 Hidden size 256 Stored precision float32 Model type dab-detr ## Identity and Version Repository IDEA-Research/dab-detr-resnet-50 Publisher IDEA-Research Task Object detection Modality Image Library transformers Parameters 44M parameters Languages en Revision d8e2856ee1f7a28088f0b8069ceebf2a44cb5042 First published 2024-05-29 Last updated 2025-01-31 ## Files and Weights 6 files, 350.5 MB in total. The weights are 2 files totalling 350.5 MB in bin, safetensors. Weights2 files · 350.5 MB Configuration2 files · 5.1 KB Documentation1 file · 13.3 KB Repository1 file · 1.5 KB Every file | File | Type | Size | SHA-256 | | --- | --- | --- | --- | | model.safetensors | Weights | 175.2 MB | 39bac44c35ef | | pytorch_model.bin | Weights | 175.3 MB | 45c7cc8a1322 | | config.json | Configuration | 4.6 KB | — | | preprocessor_config.json | Configuration | 466 B | — | | README.md | Documentation | 13.3 KB | — | | .gitattributes | Repository | 1.5 KB | — | ## License and Download License apache-2.0 Access Open weights, no gate Download size 350.5 MB [Download from IDEA-Research](https://huggingface.co/IDEA-Research/dab-detr-resnet-50) Released by IDEA-Research through its official repository on Hugging Face. [Read the license](https://www.apache.org/licenses/LICENSE-2.0). ## Built From - Described by arXiv:2201.12329 ## Memory Requirements | Precision | Weights in memory | | --- | --- | | As published | 350.5 MB | | 16-bit | 0.1 GB | | 8-bit | 0.0 GB | | 4-bit | 0.0 GB | Weights only, from the published parameter count; the key-value cache and runtime add to this. ## Questions About dab-detr-resnet-50 ### How much GPU memory does dab-detr-resnet-50 need? About 0.1 GB at 16-bit and 0 GB at 4-bit: the weights (44M parameters) plus a working margin. A long context needs more. ### What is the cheapest GPU to run dab-detr-resnet-50 on? At 16-bit, 1x MI300X from $1.85 an hour; at 4-bit, 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists. ### Can I use dab-detr-resnet-50 commercially? Yes. dab-detr-resnet-50 is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors. ## Similar Models Model · Object detection ### [conditional-detr-resnet-50](https://savrn.com/models/conditional-detr-resnet-50) [Microsoft](https://savrn.com/model-publishers/microsoft) Conditional DEtection TRansformer (DETR) model trained end-to-end on COCO 2017 object detection (118k annotated images). It was introduced in the paper Conditional DETR for Fast Training Convergence by Meng et al. and first released in this repository. The recently-developed DETR approach applies the transformer encoder and decoder architecture to object detection and achieves promising performance. In this paper, we handle the critical issue, slow training convergence, and present a conditional cross-attention mechanism for fast DETR training. 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FireViewer checkpoint terms are separate… Open weights other 43M parameters transformers [View model](https://savrn.com/models/rtdetr-v2-r50-fire-smoke) ## IDEA-Research [All models and datasets](https://savrn.com/model-publishers/idea-research) ## Versions - [d8e2856ee1f7](https://savrn.com/models/dab-detr-resnet-50/versions/d8e2856ee1f7) · current 2026-09-18 ## Explore More - [All object detection models](https://savrn.com/models/tasks/object-detection) - [All models under apache-2.0](https://savrn.com/models/licenses/apache-2-0) - [Model comparisons](https://savrn.com/models/comparisons) - [The model directory](https://savrn.com/models) - [Open model prices by host](https://savrn.com/ai-index/pricing/open-models) ## Source - Repository metadata, read 2026-10-21. - [Hugging Face record](https://huggingface.co/IDEA-Research/dab-detr-resnet-50) - [How the hub is built](https://savrn.com/model-hub/methodology)