Correct RKNN Toolkit2 conversion version

README.md

@@ -14,6 +14,6 @@ tags:
 
 Rockchip Model Zoo conversion of YOLOX Nano for RK3576 and RK3588. YOLOX Nano FP16 and INT8 models for RK3576 and RK3588. Download `model.rknn` and `metadata.yaml` from the same directory under `models/detect/yolox_nano/<chip>/<precision>/`. The [manifest](manifest.json) records each model hash.
 
-The [original YOLOX Nano checkpoint](https://github.com/Megvii-BaseDetection/YOLOX/releases/download/0.1.1rc0/yolox_nano.pth) is included under [source](tree/main/source). It was exported to ONNX with the [Rockchip YOLOX exporter](https://github.com/airockchip/YOLOX/tree/fc69c1e2ccb30fce7e18250bddc13a68090dca09) and compiled with the [Model Zoo YOLOX converter](https://github.com/airockchip/rknn_model_zoo/tree/837db8e992815ff8647eadb709f07067f4bc3a71/examples/yolox) using RKNN Toolkit2 2.3.2. The conversion changed the model format and quantized the INT8 variant.
+The [original YOLOX Nano checkpoint](https://github.com/Megvii-BaseDetection/YOLOX/releases/download/0.1.1rc0/yolox_nano.pth) is included under [source](tree/main/source). It was exported to ONNX with the [Rockchip YOLOX exporter](https://github.com/airockchip/YOLOX/tree/fc69c1e2ccb30fce7e18250bddc13a68090dca09) and compiled with the [Model Zoo YOLOX converter](https://github.com/airockchip/rknn_model_zoo/tree/837db8e992815ff8647eadb709f07067f4bc3a71/examples/yolox) using RKNN Toolkit2 2.5.0. The conversion changed the model format and quantized the INT8 variant.
 
 YOLOX is from [Megvii-BaseDetection](https://github.com/Megvii-BaseDetection/YOLOX). The [Apache-2.0 license](LICENSE) applies to this distribution.