Map model_type and doc pages names (#14944)

* Map model_type and doc pages names

* Add script

* Fix typo

* Quality

* Manual check for Auto

Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>

docs/source/model_doc/vision-encoder-decoder.mdx

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+<!--Copyright 2021 The HuggingFace Team. All rights reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
+the License. You may obtain a copy of the License at
+
+http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
+an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
+specific language governing permissions and limitations under the License.
+-->
+
+# Vision Encoder Decoder Models
+
+The [`VisionEncoderDecoderModel`] can be used to initialize an image-to-text-sequence model with any
+pretrained vision autoencoding model as the encoder (*e.g.* [ViT](vit), [BEiT](beit), [DeiT](deit))
+and any pretrained language model as the decoder (*e.g.* [RoBERTa](roberta), [GPT2](gpt2), [BERT](bert)).
+
+The effectiveness of initializing image-to-text-sequence models with pretrained checkpoints has been shown in (for
+example) [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.
+
+An example of how to use a [`VisionEncoderDecoderModel`] for inference can be seen in [TrOCR](trocr).
+
+
+## VisionEncoderDecoderConfig
+
+[[autodoc]] VisionEncoderDecoderConfig
+
+## VisionEncoderDecoderModel
+
+[[autodoc]] VisionEncoderDecoderModel
+    - forward
+    - from_encoder_decoder_pretrained
+
+## FlaxVisionEncoderDecoderModel
+
+[[autodoc]] FlaxVisionEncoderDecoderModel
+    - __call__
+    - from_encoder_decoder_pretrained