Migrate doc files to Markdown. (#24376)

* Rename index.mdx to index.md

* With saved modifs

* Address review comment

* Treat all files

* .mdx -> .md

* Remove special char

* Update utils/tests_fetcher.py

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

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

docs/source/en/model_doc/flan-t5.md

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+<!--Copyright 2022 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
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+http://www.apache.org/licenses/LICENSE-2.0
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+Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
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+specific language governing permissions and limitations under the License.
+
+⚠️ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not be
+rendered properly in your Markdown viewer.
+
+-->
+
+# FLAN-T5
+
+## Overview
+
+FLAN-T5 was released in the paper [Scaling Instruction-Finetuned Language Models](https://arxiv.org/pdf/2210.11416.pdf) - it is an enhanced version of T5 that has been finetuned in a mixture of tasks.
+
+One can directly use FLAN-T5 weights without finetuning the model:
+
+```python
+>>> from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+
+>>> model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-small")
+>>> tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-small")
+
+>>> inputs = tokenizer("A step by step recipe to make bolognese pasta:", return_tensors="pt")
+>>> outputs = model.generate(**inputs)
+>>> print(tokenizer.batch_decode(outputs, skip_special_tokens=True))
+['Pour a cup of bolognese into a large bowl and add the pasta']
+```
+
+FLAN-T5 includes the same improvements as T5 version 1.1 (see [here](https://huggingface.co/docs/transformers/model_doc/t5v1.1) for the full details of the model's improvements.)
+
+Google has released the following variants:
+
+- [google/flan-t5-small](https://huggingface.co/google/flan-t5-small)
+
+- [google/flan-t5-base](https://huggingface.co/google/flan-t5-base)
+
+- [google/flan-t5-large](https://huggingface.co/google/flan-t5-large)
+
+- [google/flan-t5-xl](https://huggingface.co/google/flan-t5-xl)
+
+- [google/flan-t5-xxl](https://huggingface.co/google/flan-t5-xxl).
+
+One can refer to [T5's documentation page](t5) for all tips, code examples and notebooks. As well as the FLAN-T5 model card for more details regarding training and evaluation of the model.
+
+The original checkpoints can be found [here](https://github.com/google-research/t5x/blob/main/docs/models.md#flan-t5-checkpoints).