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Add resources (#20296)

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Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
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NielsRogge
2022-11-21 18:24:32 +01:00
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docs/source/en/model_doc/table-transformer.mdx
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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). - 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).
- One can use the [`AutoFeatureExtractor`] API to prepare images and optional targets for the model. This will load a [`DetrFeatureExtractor`] behind the scenes. - One can use the [`AutoFeatureExtractor`] API to prepare images and optional targets for the model. This will load a [`DetrFeatureExtractor`] behind the scenes.
- A demo notebook for the Table Transformer can be found [here](https://github.com/NielsRogge/Transformers-Tutorials/tree/master/Table Transformer).
<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/model_doc/table_transformer_architecture.jpeg" <img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/model_doc/table_transformer_architecture.jpeg"
alt="drawing" width="600"/> alt="drawing" width="600"/>
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This model was contributed by [nielsr](https://huggingface.co/nielsr). The original code can be This model was contributed by [nielsr](https://huggingface.co/nielsr). The original code can be
found [here](https://github.com/microsoft/table-transformer). found [here](https://github.com/microsoft/table-transformer).
## Resources
<PipelineTag pipeline="object-detection"/>
- A demo notebook for the Table Transformer can be found [here](https://github.com/NielsRogge/Transformers-Tutorials/tree/master/Table%20Transformer).
- It turns out padding of images is quite important for detection. An interesting Github thread with replies from the authors can be found [here](https://github.com/microsoft/table-transformer/issues/68).
## TableTransformerConfig ## TableTransformerConfig