update README.md

Author: DefTruth

README.md

@@ -23,7 +23,7 @@
 
 <div id="lite.ai.toolkit-Introduction"></div> 
 
-*Lite.AI.ToolKit* 🚀🚀🌟 is a simple and user-friendly C++ library of *[70+](https://github.com/DefTruth/lite.ai.toolkit/tree/main/docs/hub/lite.ai.toolkit.hub.onnx.md)* awesome 🔥🔥🔥 AI models. It's a collection of personal interests. such as YOLOX, YoloV5, YoloV4, DeepLabV3, ArcFace, etc. *Lite.AI.ToolKit* based on *[onnxruntime c++](https://github.com/microsoft/onnxruntime)* by default. I do have plans to reimplement it with *[ncnn](https://github.com/Tencent/ncnn)* and *[MNN](https://github.com/alibaba/MNN)*, but not coming soon. It includes [object detection](#lite.ai.toolkit-object-detection), [face detection](#lite.ai.toolkit-face-detection), [style transfer](#lite.ai.toolkit-style-transfer), [face alignment](#lite.ai.toolkit-face-alignment), [face recognition](#lite.ai.toolkit-face-recognition), [segmentation](#lite.ai.toolkit-segmentation), [colorization](#lite.ai.toolkit-colorization), [face attributes analysis](#lite.ai.toolkit-face-attributes-analysis), [matting](#lite.ai.toolkit-matting), etc. You can use these awesome models simply through *lite::cv::Type::Class* syntax, such as *[lite::cv::detection::YoloV5](#lite.ai.toolkit-object-detection)*.
+*Lite.AI.ToolKit* 🚀🚀🌟 is a simple and user-friendly C++ library of *[70+](https://github.com/DefTruth/lite.ai.toolkit/tree/main/docs/hub/lite.ai.toolkit.hub.onnx.md)* awesome 🔥🔥🔥 AI models. It's a collection of personal interests. such as YOLOX, YoloV5, YoloV4, DeepLabV3, ArcFace, etc. *Lite.AI.ToolKit* based on *[onnxruntime c++](https://github.com/microsoft/onnxruntime)* by default. I do have plans to reimplement it with *[ncnn](https://github.com/Tencent/ncnn)* and *[MNN](https://github.com/alibaba/MNN)*, but not coming soon. It includes [object detection](#lite.ai.toolkit-object-detection), [face detection](#lite.ai.toolkit-face-detection), [style transfer](#lite.ai.toolkit-style-transfer), [face alignment](#lite.ai.toolkit-face-alignment), [face recognition](#lite.ai.toolkit-face-recognition), [segmentation](#lite.ai.toolkit-segmentation), [colorization](#lite.ai.toolkit-colorization), [matting](#lite.ai.toolkit-matting), etc. You can use these awesome models simply through *lite::cv::Type::Class* syntax, such as *[lite::cv::detection::YoloV5](#lite.ai.toolkit-object-detection)*.
 
 ## Citations.