Update actions

README.md

@@ -153,22 +153,22 @@ python train.py --data coco.yaml --epochs 300 --weights '' --cfg yolov5n.yaml  -
 <details open>
 <summary>Tutorials</summary>
 
-- [Train Custom Data](https://docs.ultralytics.com/yolov5/train_custom_data) 🚀 RECOMMENDED
-- [Tips for Best Training Results](https://docs.ultralytics.com/yolov5/tips_for_best_training_results) ☘️ RECOMMENDED
-- [Multi-GPU Training](https://docs.ultralytics.com/yolov5/multi_gpu_training)
-- [PyTorch Hub](https://docs.ultralytics.com/yolov5/pytorch_hub) 🌟 NEW
-- [TFLite, ONNX, CoreML, TensorRT Export](https://docs.ultralytics.com/yolov5/export) 🚀
-- [NVIDIA Jetson platform Deployment](https://docs.ultralytics.com/yolov5/jetson_nano) 🌟 NEW
-- [Test-Time Augmentation (TTA)](https://docs.ultralytics.com/yolov5/tta)
-- [Model Ensembling](https://docs.ultralytics.com/yolov5/ensemble)
-- [Model Pruning/Sparsity](https://docs.ultralytics.com/yolov5/pruning_sparsity)
-- [Hyperparameter Evolution](https://docs.ultralytics.com/yolov5/hyp_evolution)
-- [Transfer Learning with Frozen Layers](https://docs.ultralytics.com/yolov5/transfer_learn_frozen)
-- [Architecture Summary](https://docs.ultralytics.com/yolov5/architecture) 🌟 NEW
-- [Roboflow for Datasets](https://docs.ultralytics.com/yolov5/roboflow)
-- [ClearML Logging](https://docs.ultralytics.com/yolov5/clearml) 🌟 NEW
-- [YOLOv5 with Neural Magic's Deepsparse](https://docs.ultralytics.com/yolov5/neural_magic) 🌟 NEW
-- [Comet Logging](https://docs.ultralytics.com/yolov5/comet) 🌟 NEW
+* [Train Custom Data](https://docs.ultralytics.com/yolov5/tutorials/train_custom_data) 🚀 RECOMMENDED
+* [Tips for Best Training Results](https://docs.ultralytics.com/yolov5/tutorials/tips_for_best_training_results) ☘️
+* [Multi-GPU Training](https://docs.ultralytics.com/yolov5/tutorials/multi_gpu_training)
+* [PyTorch Hub](https://docs.ultralytics.com/yolov5/tutorials/pytorch_hub_model_loading) 🌟 NEW
+* [TFLite, ONNX, CoreML, TensorRT Export](https://docs.ultralytics.com/yolov5/tutorials/model_export) 🚀
+* [NVIDIA Jetson platform Deployment](https://docs.ultralytics.com/yolov5/tutorials/running_on_jetson_nano) 🌟 NEW
+* [Test-Time Augmentation (TTA)](https://docs.ultralytics.com/yolov5/tutorials/test_time_augmentation)
+* [Model Ensembling](https://docs.ultralytics.com/yolov5/tutorials/model_ensembling)
+* [Model Pruning/Sparsity](https://docs.ultralytics.com/yolov5/tutorials/model_pruning_and_sparsity)
+* [Hyperparameter Evolution](https://docs.ultralytics.com/yolov5/tutorials/hyperparameter_evolution)
+* [Transfer Learning with Frozen Layers](https://docs.ultralytics.com/yolov5/tutorials/transfer_learning_with_frozen_layers)
+* [Architecture Summary](https://docs.ultralytics.com/yolov5/tutorials/architecture_description) 🌟 NEW
+* [Roboflow for Datasets, Labeling, and Active Learning](https://docs.ultralytics.com/yolov5/tutorials/roboflow_datasets_integration)
+* [ClearML Logging](https://docs.ultralytics.com/yolov5/tutorials/clearml_logging_integration) 🌟 NEW
+* [YOLOv5 with Neural Magic's Deepsparse](https://docs.ultralytics.com/yolov5/tutorials/neural_magic_pruning_quantization) 🌟 NEW
+* [Comet Logging](https://docs.ultralytics.com/yolov5/tutorials/comet_logging_integration) 🌟 NEW
 
 </details>
 
@@ -436,10 +436,10 @@ Get started in seconds with our verified environments. Click each icon below for
   <a href="https://hub.docker.com/r/ultralytics/yolov5">
     <img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-docker-small.png" width="10%" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="5%" alt="" />
-  <a href="https://github.com/ultralytics/yolov5/wiki/AWS-Quickstart">
+  <a href="https://docs.ultralytics.com/yolov5/environments/aws_quickstart_tutorial/">
     <img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-aws-small.png" width="10%" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="5%" alt="" />
-  <a href="https://github.com/ultralytics/yolov5/wiki/GCP-Quickstart">
+  <a href="https://docs.ultralytics.com/yolov5/environments/google_cloud_quickstart_tutorial/">
     <img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-gcp-small.png" width="10%" /></a>
 </div>
 

README.zh-CN.md

@@ -147,22 +147,22 @@ python train.py --data coco.yaml --epochs 300 --weights '' --cfg yolov5n.yaml  -
 <details open>
 <summary>教程</summary>
 
-- [训练自定义数据](https://docs.ultralytics.com/yolov5/train_custom_data) 🚀 推荐
-- [获得最佳训练结果的技巧](https://docs.ultralytics.com/yolov5/tips_for_best_training_results) ☘️ 推荐
-- [多 GPU 训练](https://docs.ultralytics.com/yolov5/multi_gpu_training)
-- [PyTorch Hub](https://docs.ultralytics.com/yolov5/pytorch_hub) 🌟 新
-- [TFLite, ONNX, CoreML, TensorRT 导出](https://docs.ultralytics.com/yolov5/export) 🚀
-- [NVIDIA Jetson 平台部署](https://docs.ultralytics.com/yolov5/jetson_nano) 🌟 新
-- [测试时增强（TTA）](https://docs.ultralytics.com/yolov5/tta)
-- [模型集成](https://docs.ultralytics.com/yolov5/ensemble)
-- [模型剪枝/稀疏性](https://docs.ultralytics.com/yolov5/pruning_sparsity)
-- [超参数进化](https://docs.ultralytics.com/yolov5/hyp_evolution)
-- [冻结层的迁移学习](https://docs.ultralytics.com/yolov5/transfer_learn_frozen)
-- [架构概述](https://docs.ultralytics.com/yolov5/architecture) 🌟 新
-- [Roboflow](https://docs.ultralytics.com/yolov5/roboflow)
-- [ClearML 日志记录](https://docs.ultralytics.com/yolov5/clearml) 🌟 新
-- [YOLOv5 与 Neural Magic 的 Deepsparse](https://docs.ultralytics.com/yolov5/neural_magic) 🌟 新
-- [Comet 日志记录](https://docs.ultralytics.com/yolov5/comet) 🌟 新
+* [训练自定义数据](https://docs.ultralytics.com/yolov5/tutorials/train_custom_data) 🚀 推荐
+* [获得最佳训练结果的技巧](https://docs.ultralytics.com/yolov5/tutorials/tips_for_best_training_results) ☘️
+* [多GPU训练](https://docs.ultralytics.com/yolov5/tutorials/multi_gpu_training)
+* [PyTorch Hub](https://docs.ultralytics.com/yolov5/tutorials/pytorch_hub_model_loading) 🌟 新
+* [TFLite，ONNX，CoreML，TensorRT导出](https://docs.ultralytics.com/yolov5/tutorials/model_export) 🚀
+* [NVIDIA Jetson平台部署](https://docs.ultralytics.com/yolov5/tutorials/running_on_jetson_nano) 🌟 新
+* [测试时增强 (TTA)](https://docs.ultralytics.com/yolov5/tutorials/test_time_augmentation)
+* [模型集成](https://docs.ultralytics.com/yolov5/tutorials/model_ensembling)
+* [模型剪枝/稀疏](https://docs.ultralytics.com/yolov5/tutorials/model_pruning_and_sparsity)
+* [超参数进化](https://docs.ultralytics.com/yolov5/tutorials/hyperparameter_evolution)
+* [冻结层的迁移学习](https://docs.ultralytics.com/yolov5/tutorials/transfer_learning_with_frozen_layers)
+* [架构概述](https://docs.ultralytics.com/yolov5/tutorials/architecture_description) 🌟 新
+* [Roboflow用于数据集、标注和主动学习](https://docs.ultralytics.com/yolov5/tutorials/roboflow_datasets_integration)
+* [ClearML日志记录](https://docs.ultralytics.com/yolov5/tutorials/clearml_logging_integration) 🌟 新
+* [使用Neural Magic的Deepsparse的YOLOv5](https://docs.ultralytics.com/yolov5/tutorials/neural_magic_pruning_quantization) 🌟 新
+* [Comet日志记录](https://docs.ultralytics.com/yolov5/tutorials/comet_logging_integration) 🌟 新
 
 </details>
 
@@ -399,9 +399,7 @@ python classify/predict.py --weights yolov5s-cls.pt --data data/images/bus.jpg
 ```
 
 ```python
-model = torch.hub.load(
-    "ultralytics/yolov5", "custom", "yolov5s-cls.pt"
-)  # load from PyTorch Hub
+model = torch.hub.load("ultralytics/yolov5", "custom", "yolov5s-cls.pt")  # load from PyTorch Hub
 ```
 
 ### 模型导出
@@ -431,10 +429,10 @@ python export.py --weights yolov5s-cls.pt resnet50.pt efficientnet_b0.pt --inclu
   <a href="https://hub.docker.com/r/ultralytics/yolov5">
     <img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-docker-small.png" width="10%" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="5%" alt="" />
-  <a href="https://github.com/ultralytics/yolov5/wiki/AWS-Quickstart">
+  <a href="https://docs.ultralytics.com/yolov5/environments/aws_quickstart_tutorial/">
     <img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-aws-small.png" width="10%" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="5%" alt="" />
-  <a href="https://github.com/ultralytics/yolov5/wiki/GCP-Quickstart">
+  <a href="https://docs.ultralytics.com/yolov5/environments/google_cloud_quickstart_tutorial/">
     <img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-gcp-small.png" width="10%" /></a>
 </div>