[Docs] Model_doc structure/clarity improvements (#26876)
* first batch of structure improvements for model_docs * second batch of structure improvements for model_docs * more structure improvements for model_docs * more structure improvements for model_docs * structure improvements for cv model_docs * more structural refactoring * addressed feedback about image processors
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@@ -33,16 +33,15 @@ significant increase in training performance and a more reliable estimate of mod
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object detection models trained on PubTables-1M produce excellent results for all three tasks of detection, structure recognition, and functional analysis without the need for any
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special customization for these tasks.*
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Tips:
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- The authors released 2 models, one for [table detection](https://huggingface.co/microsoft/table-transformer-detection) in documents, one for [table structure recognition](https://huggingface.co/microsoft/table-transformer-structure-recognition) (the task of recognizing the individual rows, columns etc. in a table).
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- One can use the [`AutoImageProcessor`] API to prepare images and optional targets for the model. This will load a [`DetrImageProcessor`] behind the scenes.
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<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/model_doc/table_transformer_architecture.jpeg"
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alt="drawing" width="600"/>
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<small> Table detection and table structure recognition clarified. Taken from the <a href="https://arxiv.org/abs/2110.00061">original paper</a>. </small>
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The authors released 2 models, one for [table detection](https://huggingface.co/microsoft/table-transformer-detection) in
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documents, one for [table structure recognition](https://huggingface.co/microsoft/table-transformer-structure-recognition)
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(the task of recognizing the individual rows, columns etc. in a table).
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This model was contributed by [nielsr](https://huggingface.co/nielsr). The original code can be
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found [here](https://github.com/microsoft/table-transformer).
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