Convert model files from rst to mdx (#14865)

* First pass

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Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

docs/source/model_doc/gpt_neo.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
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+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.
+-->
+
+# GPT Neo
+
+## Overview
+
+The GPTNeo model was released in the [EleutherAI/gpt-neo](https://github.com/EleutherAI/gpt-neo) repository by Sid
+Black, Stella Biderman, Leo Gao, Phil Wang and Connor Leahy. It is a GPT2 like causal language model trained on the
+[Pile](https://pile.eleuther.ai/) dataset.
+
+The architecture is similar to GPT2 except that GPT Neo uses local attention in every other layer with a window size of
+256 tokens.
+
+This model was contributed by [valhalla](https://huggingface.co/valhalla).
+
+### Generation
+
+The `generate()` method can be used to generate text using GPT Neo model.
+
+```python
+>>> from transformers import GPTNeoForCausalLM, GPT2Tokenizer
+>>> model = GPTNeoForCausalLM.from_pretrained("EleutherAI/gpt-neo-1.3B")
+>>> tokenizer = GPT2Tokenizer.from_pretrained("EleutherAI/gpt-neo-1.3B")
+
+>>> prompt = "In a shocking finding, scientists discovered a herd of unicorns living in a remote, " \
+...          "previously unexplored valley, in the Andes Mountains. Even more surprising to the " \
+...          "researchers was the fact that the unicorns spoke perfect English."
+
+>>> input_ids = tokenizer(prompt, return_tensors="pt").input_ids
+
+>>> gen_tokens = model.generate(input_ids, do_sample=True, temperature=0.9, max_length=100,)
+>>> gen_text = tokenizer.batch_decode(gen_tokens)[0]
+```
+
+## GPTNeoConfig
+
+[[autodoc]] GPTNeoConfig
+
+## GPTNeoModel
+
+[[autodoc]] GPTNeoModel
+    - forward
+
+## GPTNeoForCausalLM
+
+[[autodoc]] GPTNeoForCausalLM
+    - forward
+
+## GPTNeoForSequenceClassification
+
+[[autodoc]] GPTNeoForSequenceClassification
+    - forward
+
+## FlaxGPTNeoModel
+
+[[autodoc]] FlaxGPTNeoModel
+    - __call__
+
+## FlaxGPTNeoForCausalLM
+
+[[autodoc]] FlaxGPTNeoForCausalLM
+    - __call__