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lines changed Original file line number Diff line number Diff line change @@ -376,8 +376,8 @@ In addition to supporting any model from HuggingFace Transfomers and MMDetection
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Task | model architectures | String literal syntax
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-- - | ---------- | ----------
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Image classification< br> (multi- class and multi- label)| ** [BEiT](https:// ml.azure.com/ registries/ azureml- preview/ models/ microsoft- beit- base- patch16- 224 - pt22k- ft22k/ version/ 2 )** < br> ** [ViT](https:// ml.azure.com/ registries/ azureml- preview/ models/ google- vit- base- patch16- 224 / version/ 2 )** < br> ** [DeiT](https:// ml.azure.com/ registries/ azureml- preview/ models/ facebook- deit- base- patch16- 224 / version/ 2 )** < br> ** [SwinV2](https:// ml.azure.com/ registries/ azureml- preview/ models/ microsoft- swinv2- base- patch4- window12- 192 - 22k / version/ 2 )** < br> TODO update links to staging registry | `microsoft/ beit- base- patch16- 224 - pt22k- ft22k` < br> `google/ vit- base- patch16- 224 ` < br> `facebook/ deit- base- patch16- 224 ` < br> `microsoft/ swinv2- base- patch4- window12- 192 - 22k `
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- Object Detection | TODO | `sparse_rcnn_r50_fpn_300_proposals_crop_mstrain_480- 800_3x_coco ` < br> `sparse_rcnn_r101_fpn_300_proposals_crop_mstrain_480- 800_3x_coco ` < br> `deformable_detr_twostage_refine_r50_16x2_50e_coco` < br> `vfnet_r50_fpn_mdconv_c3- c5_mstrain_2x_coco` < br> `vfnet_x101_64x4d_fpn_mdconv_c3- c5_mstrain_2x_coco` < br> `yolof_r50_c5_8x8_1x_coco` < br> `mask_rcnn_swin- t- p4- w7_fpn_fp16_ms- crop- 3x_coco `
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- Instance Segmentation | TODO | TODO
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+ Object Detection | ** [Sparse R - CNN ]() ** < br > ** [Deformable DETR ]() ** < br > ** [VFNet]() ** < br > ** [ YOLOF ]() ** < br > ** [Swin]() ** < br > TODO update links to staging registry | `sparse_rcnn_r50_fpn_300_proposals_crop_mstrain_480- 800_3x_coco ` < br> `sparse_rcnn_r101_fpn_300_proposals_crop_mstrain_480- 800_3x_coco ` < br> `deformable_detr_twostage_refine_r50_16x2_50e_coco` < br> `vfnet_r50_fpn_mdconv_c3- c5_mstrain_2x_coco` < br> `vfnet_x101_64x4d_fpn_mdconv_c3- c5_mstrain_2x_coco` < br> `yolof_r50_c5_8x8_1x_coco` < br> `mask_rcnn_swin- t- p4- w7_fpn_fp16_ms- crop- 3x_coco `
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+ Instance Segmentation | ** [Swin]() ** < br > TODO update links to staging registry | `mask_rcnn_swin - t - p4 - w7_fpn_1x_coco`
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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 :
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