Merge pull request #259972 from bhimar/mmd-3x-doc-updates

Mmd 3x doc updates for AutoML Images

Author: prmerger-automator[bot]

articles/machine-learning/how-to-auto-train-image-models.md

@@ -369,20 +369,20 @@ Instance segmentation | **MaskRCNN ResNet FPN**| `maskrcnn_resnet18_fpn` <br> `m
 
 #### Supported model architectures - HuggingFace and MMDetection (preview)
 
-With the new backend that runs on [Azure Machine Learning pipelines](concept-ml-pipelines.md), you can additionally use any image classification model from the [HuggingFace Hub](https://huggingface.co/models?pipeline_tag=image-classification&library=transformers) which is part of the transformers library (such as microsoft/beit-base-patch16-224), as well as any object detection or instance segmentation model from the [MMDetection Version 2.28.2 Model Zoo](https://mmdetection.readthedocs.io/en/v2.28.2/model_zoo.html) (such as atss_r50_fpn_1x_coco). 
+With the new backend that runs on [Azure Machine Learning pipelines](concept-ml-pipelines.md), you can additionally use any image classification model from the [HuggingFace Hub](https://huggingface.co/models?pipeline_tag=image-classification&library=transformers) which is part of the transformers library (such as microsoft/beit-base-patch16-224), as well as any object detection or instance segmentation model from the [MMDetection Version 3.1.0 Model Zoo](https://mmdetection.readthedocs.io/en/v3.1.0/model_zoo.html) (such as `atss_r50_fpn_1x_coco`). 
 
-In addition to supporting any model from HuggingFace Transfomers and MMDetection 2.28.2, we also offer a list of curated models from these libraries in the azureml-staging registry. These curated models have been tested thoroughly and use default hyperparameters selected from extensive benchmarking to ensure effective training. The table below summarizes these curated models.
+In addition to supporting any model from HuggingFace Transfomers and MMDetection 3.1.0, we also offer a list of curated models from these libraries in the azureml registry. These curated models have been tested thoroughly and use default hyperparameters selected from extensive benchmarking to ensure effective training. The table below summarizes these curated models.
 
 Task |  model architectures | String literal syntax
 ---|----------|----------
-Image classification<br> (multi-class and multi-label)| **BEiT** <br> **ViT** <br> **DeiT** <br> **SwinV2]** | [`microsoft/beit-base-patch16-224-pt22k-ft22k`](https://ml.azure.com/registries/azureml/models/microsoft-beit-base-patch16-224-pt22k-ft22k/version/5)<br> [`google/vit-base-patch16-224`](https://ml.azure.com/registries/azureml/models/google-vit-base-patch16-224/version/5)<br> [`facebook/deit-base-patch16-224`](https://ml.azure.com/registries/azureml/models/facebook-deit-base-patch16-224/version/5)<br> [`microsoft/swinv2-base-patch4-window12-192-22k`](https://ml.azure.com/registries/azureml/models/microsoft-swinv2-base-patch4-window12-192-22k/version/5)
-Object Detection | **Sparse R-CNN** <br> **Deformable DETR** <br> **VFNet** <br> **YOLOF** <br> **Swin** | [`sparse_rcnn_r50_fpn_300_proposals_crop_mstrain_480-800_3x_coco`](https://ml.azure.com/registries/azureml/models/sparse_rcnn_r50_fpn_300_proposals_crop_mstrain_480-800_3x_coco/version/3)<br> [`sparse_rcnn_r101_fpn_300_proposals_crop_mstrain_480-800_3x_coco`](https://ml.azure.com/registries/azureml/models/sparse_rcnn_r101_fpn_300_proposals_crop_mstrain_480-800_3x_coco/version/3) <br> [`deformable_detr_twostage_refine_r50_16x2_50e_coco`](https://ml.azure.com/registries/azureml/models/deformable_detr_twostage_refine_r50_16x2_50e_coco/version/3) <br> [`vfnet_r50_fpn_mdconv_c3-c5_mstrain_2x_coco`](https://ml.azure.com/registries/azureml/models/vfnet_r50_fpn_mdconv_c3-c5_mstrain_2x_coco/version/3) <br> [`vfnet_x101_64x4d_fpn_mdconv_c3-c5_mstrain_2x_coco`](https://ml.azure.com/registries/azureml/models/vfnet_x101_64x4d_fpn_mdconv_c3-c5_mstrain_2x_coco/version/3) <br> [`yolof_r50_c5_8x8_1x_coco`](https://ml.azure.com/registries/azureml/models/yolof_r50_c5_8x8_1x_coco/version/3)
-Instance Segmentation | **Swin** | [`mask_rcnn_swin-t-p4-w7_fpn_1x_coco`](https://ml.azure.com/registries/azureml/models/mask_rcnn_swin-t-p4-w7_fpn_1x_coco/version/3)
+Image classification<br> (multi-class and multi-label)| **BEiT** <br> **ViT** <br> **DeiT** <br> **SwinV2** | [`microsoft/beit-base-patch16-224-pt22k-ft22k`](https://ml.azure.com/registries/azureml/models/microsoft-beit-base-patch16-224-pt22k-ft22k/version/5)<br> [`google/vit-base-patch16-224`](https://ml.azure.com/registries/azureml/models/google-vit-base-patch16-224/version/5)<br> [`facebook/deit-base-patch16-224`](https://ml.azure.com/registries/azureml/models/facebook-deit-base-patch16-224/version/5)<br> [`microsoft/swinv2-base-patch4-window12-192-22k`](https://ml.azure.com/registries/azureml/models/microsoft-swinv2-base-patch4-window12-192-22k/version/5)
+Object Detection | **Sparse R-CNN** <br> **Deformable DETR** <br> **VFNet** <br> **YOLOF** <br> **Swin** | [`mmd-3x-sparse-rcnn_r50_fpn_300-proposals_crop-ms-480-800-3x_coco`](https://ml.azure.com/registries/azureml/models/mmd-3x-sparse-rcnn_r50_fpn_300-proposals_crop-ms-480-800-3x_coco/version/8)<br> [`mmd-3x-sparse-rcnn_r101_fpn_300-proposals_crop-ms-480-800-3x_coco`](https://ml.azure.com/registries/azureml/models/mmd-3x-sparse-rcnn_r101_fpn_300-proposals_crop-ms-480-800-3x_coco/version/8) <br> [`mmd-3x-deformable-detr_refine_twostage_r50_16xb2-50e_coco`](https://ml.azure.com/registries/azureml/models/mmd-3x-deformable-detr_refine_twostage_r50_16xb2-50e_coco/version/8) <br> [`mmd-3x-vfnet_r50-mdconv-c3-c5_fpn_ms-2x_coco`](https://ml.azure.com/registries/azureml/models/mmd-3x-vfnet_r50-mdconv-c3-c5_fpn_ms-2x_coco/version/8) <br> [`mmd-3x-vfnet_x101-64x4d-mdconv-c3-c5_fpn_ms-2x_coco`](https://ml.azure.com/registries/azureml/models/mmd-3x-vfnet_x101-64x4d-mdconv-c3-c5_fpn_ms-2x_coco/version/8) <br> [`mmd-3x-yolof_r50_c5_8x8_1x_coco`](https://ml.azure.com/registries/azureml/models/mmd-3x-yolof_r50_c5_8x8_1x_coco/version/8)
+Instance Segmentation | **Swin** | [`mmd-3x-mask-rcnn_swin-t-p4-w7_fpn_1x_coco`](https://ml.azure.com/registries/azureml/models/mmd-3x-mask-rcnn_swin-t-p4-w7_fpn_1x_coco/version/8)
 
 We constantly update the list of curated models. You can get the most up-to-date list of the curated models for a given task using the Python SDK:
 ```
 credential = DefaultAzureCredential()
-ml_client = MLClient(credential, registry_name="azureml-staging")
+ml_client = MLClient(credential, registry_name="azureml")
 
 models = ml_client.models.list()
 classification_models = []