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license: agpl-3.0
tags:
- rknn
- rknn2
- rockchip
- rk3576
- rk3588
---
# YOLOv8-RKNN2
> **Looking for the Ultralytics RKNN exports?** See [YOLOv8-RKNN2-Ultralytics](https://huggingface.co/HanzoHuang/YOLOv8-RKNN2-Ultralytics).
YOLOv8 RKNN exports for **RK3576** and **RK3588**, compiled with RKNN Toolkit2 2.3.2. Available tasks: detection, classification, oriented bounding boxes, pose, and instance segmentation.
## Choose a model
Models are organized by toolkit version, task, variant, target chip, and precision:
```text
models/v<toolkit-version>/<task>/<variant>/<chip>/<precision>/
```
Download `model.rknn` and `metadata.yaml` from the same directory. The [manifest](manifest.json) lists the available models and checksums.
## Conversion
The repository includes Rockchip-guided and custom exports. Detection includes n, s, and m variants in FP16 and INT8 for both chips. The checkpoints were exported with Rockchip's RKOPT detector head and compiled with the Model Zoo converter. Checkpoint URLs, exporter commits, scripts, and ONNX graphs are in [source](tree/main/source).
## Source and license
Original checkpoints, conversion scripts, and provenance are in [source](tree/main/source). The models and checkpoints are distributed under AGPL-3.0; see [LICENSE](LICENSE) and [checkpoint details](source/weights.json).
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