Renesas/YOLO12n-ONNX
object-detection model by Renesas
From the publisher
Model card & documentation
Source previewRead the publisher’s intended use, setup instructions, evaluations and limitations. The original model card is the source of truth.
This repository hosts YOLO12n, targeting the Renesas R-Car X5H platform for object-detection inference on the NPX6 NPU. The FP32 ONNX model is auto-cast to INT8 by the Renesas MWMX toolchain at compile time — no separate quantization step is required. Measured on Renesas R-Car X5H via…
Read the full model card ↗ · Preview checked 2026-09-23T08:47:24.188Z
Inside the original model card — Document outline
- YOLO12n (ONNX) – Renesas X5H
- Introduction
- Deployment Flow
- Provided Artifacts
- Performance
- Accuracy
- Runtime Details
- MWMX Runtime
- Prerequisites
- Download
- Benchmark Methodology
Headings are captured from the source. Links open the publisher’s document, not a locally hosted copy.
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
Renesas/YOLO12n-ONNX is a object-detection model repository published by Renesas on Hugging Face. A library was not reported.
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
- Not reported
- Recent downloads (30 days)
- 0
- Cumulative likes
- 0
- Hugging Face trending score
- 0
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2026-09-23T06:13:20.000Z
- Last modified
- 2026-09-23T06:13:23.000Z
Compatibility and lineage
Language coverage was not reported.
Reported base models: ultralytics/yolo12n
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 2026-09-23T06:37:25.545Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.
Related models
mudler/locate-anything.cpp-gguf
PaddlePaddle/PP-DocLayoutV3_safetensors
microsoft/table-transformer-structure-recognition