mudler/rfdetr-cpp-nano
object-detection model by mudler
From the publisher
Model card & documentation
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GGUF-format weights of Roboflow RF-DETR Nano (detection variant) for use with rfdetr.cpp, a C++/ggml implementation that matches the upstream PyTorch model on CPU. This repo contains all four standard quantizations of this variant. F16 is the recommended default — same accuracy as F32, 1.85× smaller, and typically the fastest on modern CPUs thanks to ggml's F32×F16 matmul fast path. All accuracy numbers are computed against the upstream PyTorch reference (rfdetr 1.7.0) on 7 COCO val2017 images at threshold 0.5. Latency is measured with rfdetr-cli bench (8 iters + 3 warmup) at T=8 threads on a single AMD Ryzen…
Read the full model card ↗ · Preview checked 2026-09-30T06:47:17.316Z
Inside the original model card — Document outline
- RF-DETR Nano — GGUF for rfdetr.cpp
- Available files
- Architecture
- Quantization notes
- Usage
- Accuracy methodology
- License
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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
mudler/rfdetr-cpp-nano is a object-detection model repository published by mudler on Hugging Face. The source reports the rfdetr.cpp 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
- rfdetr.cpp
- Recent downloads (30 days)
- 1,413
- Cumulative likes
- 9
- Hugging Face trending score
- 0
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2026-05-27T07:26:02.000Z
- Last modified
- 2026-05-27T07:57:47.000Z
Compatibility and lineage
Language coverage was not reported.
Reported base models: roboflow/rfdetr
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.
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-09-30T06:41:12.620Z. 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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