From 14fe3e04103fc464ed1ec7185ee99159e84456c0 Mon Sep 17 00:00:00 2001
From: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Date: Tue, 18 Oct 2022 17:42:46 +0200
Subject: [PATCH] Add docs (#19729)

Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
---
 docs/source/en/model_doc/lilt.mdx              | 4 ++--
 docs/source/en/model_doc/table-transformer.mdx | 5 +++++
 2 files changed, 7 insertions(+), 2 deletions(-)

diff --git a/docs/source/en/model_doc/lilt.mdx b/docs/source/en/model_doc/lilt.mdx
index 5dad69b3f0..9b80c1bc09 100644
--- a/docs/source/en/model_doc/lilt.mdx
+++ b/docs/source/en/model_doc/lilt.mdx
@@ -35,8 +35,8 @@ model.push_to_hub("name_of_repo_on_the_hub")
 ```
 
 - When preparing data for the model, make sure to use the token vocabulary that corresponds to the RoBERTa checkpoint you combined with the Layout Transformer.
-- As (lilt-roberta-en-base)[https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base] uses the same vocabulary as [LayoutLMv3](layoutlmv3), one can use [`LayoutLMv3TokenizerFast`] to prepare data for the model.
-The same is true for (lilt-roberta-en-base)[https://huggingface.co/SCUT-DLVCLab/lilt-infoxlm-base]: one can use [`LayoutXLMTokenizerFast`] for that model.
+- As [lilt-roberta-en-base](https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base) uses the same vocabulary as [LayoutLMv3](layoutlmv3), one can use [`LayoutLMv3TokenizerFast`] to prepare data for the model.
+The same is true for [lilt-roberta-en-base](https://huggingface.co/SCUT-DLVCLab/lilt-infoxlm-base): one can use [`LayoutXLMTokenizerFast`] for that model.
 - Demo notebooks for LiLT can be found [here](https://github.com/NielsRogge/Transformers-Tutorials/tree/master/LiLT).
 
 <img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/model_doc/lilt_architecture.jpg"
diff --git a/docs/source/en/model_doc/table-transformer.mdx b/docs/source/en/model_doc/table-transformer.mdx
index 2665e2b462..b7d27749fe 100644
--- a/docs/source/en/model_doc/table-transformer.mdx
+++ b/docs/source/en/model_doc/table-transformer.mdx
@@ -35,6 +35,11 @@ Tips:
 - 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"
+alt="drawing" width="600"/>
+
+<small> Table detection and table structure recognition clarified. Taken from the <a href="https://arxiv.org/abs/2110.00061">original paper</a>. </small>
+
 This model was contributed by [nielsr](https://huggingface.co/nielsr). The original code can be
 found [here](https://github.com/microsoft/table-transformer).