Add support for Table Transformer model

README.md

@@ -330,6 +330,7 @@ You can refine your search by selecting the task you're interested in (e.g., [te
 1. **[Swin2SR](https://huggingface.co/docs/transformers/model_doc/swin2sr)** (from University of Würzburg) released with the paper [Swin2SR: SwinV2 Transformer for Compressed Image Super-Resolution and Restoration](https://arxiv.org/abs/2209.11345) by Marcos V. Conde, Ui-Jin Choi, Maxime Burchi, Radu Timofte.
 1. **[T5](https://huggingface.co/docs/transformers/model_doc/t5)** (from Google AI) released with the paper [Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer](https://arxiv.org/abs/1910.10683) by Colin Raffel and Noam Shazeer and Adam Roberts and Katherine Lee and Sharan Narang and Michael Matena and Yanqi Zhou and Wei Li and Peter J. Liu.
 1. **[T5v1.1](https://huggingface.co/docs/transformers/model_doc/t5v1.1)** (from Google AI) released in the repository [google-research/text-to-text-transfer-transformer](https://github.com/google-research/text-to-text-transfer-transformer/blob/main/released_checkpoints.md#t511) by Colin Raffel and Noam Shazeer and Adam Roberts and Katherine Lee and Sharan Narang and Michael Matena and Yanqi Zhou and Wei Li and Peter J. Liu.
+1. **[Table Transformer](https://huggingface.co/docs/transformers/model_doc/table-transformer)** (from Microsoft Research) released with the paper [PubTables-1M: Towards Comprehensive Table Extraction From Unstructured Documents](https://arxiv.org/abs/2110.00061) by Brandon Smock, Rohith Pesala, Robin Abraham.
 1. **[TrOCR](https://huggingface.co/docs/transformers/model_doc/trocr)** (from Microsoft), released together with the paper [TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models](https://arxiv.org/abs/2109.10282) by Minghao Li, Tengchao Lv, Lei Cui, Yijuan Lu, Dinei Florencio, Cha Zhang, Zhoujun Li, Furu Wei.
 1. **[Vision Transformer (ViT)](https://huggingface.co/docs/transformers/model_doc/vit)** (from Google AI) released with the paper [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://arxiv.org/abs/2010.11929) by Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, Neil Houlsby.
 1. **[ViTMatte](https://huggingface.co/docs/transformers/model_doc/vitmatte)** (from HUST-VL) released with the paper [ViTMatte: Boosting Image Matting with Pretrained Plain Vision Transformers](https://arxiv.org/abs/2305.15272) by Jingfeng Yao, Xinggang Wang, Shusheng Yang, Baoyuan Wang.

docs/snippets/6_supported-models.snippet

@@ -65,6 +65,7 @@
 1. **[Swin2SR](https://huggingface.co/docs/transformers/model_doc/swin2sr)** (from University of Würzburg) released with the paper [Swin2SR: SwinV2 Transformer for Compressed Image Super-Resolution and Restoration](https://arxiv.org/abs/2209.11345) by Marcos V. Conde, Ui-Jin Choi, Maxime Burchi, Radu Timofte.
 1. **[T5](https://huggingface.co/docs/transformers/model_doc/t5)** (from Google AI) released with the paper [Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer](https://arxiv.org/abs/1910.10683) by Colin Raffel and Noam Shazeer and Adam Roberts and Katherine Lee and Sharan Narang and Michael Matena and Yanqi Zhou and Wei Li and Peter J. Liu.
 1. **[T5v1.1](https://huggingface.co/docs/transformers/model_doc/t5v1.1)** (from Google AI) released in the repository [google-research/text-to-text-transfer-transformer](https://github.com/google-research/text-to-text-transfer-transformer/blob/main/released_checkpoints.md#t511) by Colin Raffel and Noam Shazeer and Adam Roberts and Katherine Lee and Sharan Narang and Michael Matena and Yanqi Zhou and Wei Li and Peter J. Liu.
+1. **[Table Transformer](https://huggingface.co/docs/transformers/model_doc/table-transformer)** (from Microsoft Research) released with the paper [PubTables-1M: Towards Comprehensive Table Extraction From Unstructured Documents](https://arxiv.org/abs/2110.00061) by Brandon Smock, Rohith Pesala, Robin Abraham.
 1. **[TrOCR](https://huggingface.co/docs/transformers/model_doc/trocr)** (from Microsoft), released together with the paper [TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models](https://arxiv.org/abs/2109.10282) by Minghao Li, Tengchao Lv, Lei Cui, Yijuan Lu, Dinei Florencio, Cha Zhang, Zhoujun Li, Furu Wei.
 1. **[Vision Transformer (ViT)](https://huggingface.co/docs/transformers/model_doc/vit)** (from Google AI) released with the paper [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://arxiv.org/abs/2010.11929) by Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, Neil Houlsby.
 1. **[ViTMatte](https://huggingface.co/docs/transformers/model_doc/vitmatte)** (from HUST-VL) released with the paper [ViTMatte: Boosting Image Matting with Pretrained Plain Vision Transformers](https://arxiv.org/abs/2305.15272) by Jingfeng Yao, Xinggang Wang, Shusheng Yang, Baoyuan Wang.

scripts/supported_models.py

@@ -756,6 +756,16 @@
             'hkunlp/instructor-large',
         ],
     },
+    'table-transformer': {
+        # Object detection
+        'object-detection': [
+            'microsoft/table-transformer-detection',
+            'microsoft/table-transformer-structure-recognition',
+            'microsoft/table-transformer-structure-recognition-v1.1-all',
+            'microsoft/table-transformer-structure-recognition-v1.1-fin',
+            'microsoft/table-transformer-structure-recognition-v1.1-pub',
+        ],
+    },
     'trocr': {  # NOTE: also a `vision-encoder-decoder`
         # Text-to-image
         'text-to-image': [

src/models.js

@@ -3606,6 +3606,30 @@ export class DetrSegmentationOutput extends ModelOutput {
 }
 //////////////////////////////////////////////////
 
+//////////////////////////////////////////////////
+export class TableTransformerPreTrainedModel extends PreTrainedModel { }
+
+/**
+ * The bare Table Transformer Model (consisting of a backbone and encoder-decoder Transformer)
+ * outputting raw hidden-states without any specific head on top.
+ */
+export class TableTransformerModel extends TableTransformerPreTrainedModel { }
+
+/**
+ * Table Transformer Model (consisting of a backbone and encoder-decoder Transformer)
+ * with object detection heads on top, for tasks such as COCO detection.
+ */
+export class TableTransformerForObjectDetection extends TableTransformerPreTrainedModel {
+    /**
+     * @param {any} model_inputs
+     */
+    async _call(model_inputs) {
+        return new TableTransformerObjectDetectionOutput(await super._call(model_inputs));
+    }
+}
+export class TableTransformerObjectDetectionOutput extends DetrObjectDetectionOutput { }
+//////////////////////////////////////////////////
+
 
 //////////////////////////////////////////////////
 export class DeiTPreTrainedModel extends PreTrainedModel { }
@@ -4694,6 +4718,7 @@ const MODEL_MAPPING_NAMES_ENCODER_ONLY = new Map([
     ['audio-spectrogram-transformer', ['ASTModel', ASTModel]],
 
     ['detr', ['DetrModel', DetrModel]],
+    ['table-transformer', ['TableTransformerModel', TableTransformerModel]],
     ['vit', ['ViTModel', ViTModel]],
     ['mobilevit', ['MobileViTModel', MobileViTModel]],
     ['owlvit', ['OwlViTModel', OwlViTModel]],
@@ -4876,6 +4901,7 @@ const MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES = new Map([
 
 const MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES = new Map([
     ['detr', ['DetrForObjectDetection', DetrForObjectDetection]],
+    ['table-transformer', ['TableTransformerForObjectDetection', TableTransformerForObjectDetection]],
     ['yolos', ['YolosForObjectDetection', YolosForObjectDetection]],
 ]);