[model_cards] Migrate cards from this repo to model repos on huggingface.co (#9013)

* rm all model cards

* Update the .rst

@sgugger it is still not super crystal clear/streamlined so let me know if any ideas to make it simpler

* Add a rootlevel README.md with simple instructions/context

* Update docs/source/model_sharing.rst
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* make style

* rm all model cards
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

model_cards/google/bert2bert_L-24_wmt_de_en/README.md

----
-language: 
-- en
-- de
-license: apache-2.0
-datasets:
-- wmt14
-tags:
-- translation
----
-
-# bert2bert_L-24_wmt_de_en EncoderDecoder model
-
-The model was introduced in 
-[this paper](https://arxiv.org/abs/1907.12461) by Sascha Rothe, Shashi Narayan, Aliaksei Severyn and first released in [this repository](https://tfhub.dev/google/bertseq2seq/bert24_de_en/1). 
-
-The model is an encoder-decoder model that was initialized on the `bert-large` checkpoints for both the encoder 
-and decoder and fine-tuned on German to English translation on the WMT dataset, which is linked above.
-
-Disclaimer: The model card has been written by the Hugging Face team.
-
-## How to use
-
-You can use this model for translation, *e.g.*
-
-```python
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
-
-tokenizer = AutoTokenizer.from_pretrained("google/bert2bert_L-24_wmt_de_en", pad_token="<pad>", eos_token="</s>", bos_token="<s>")
-model = AutoModelForSeq2SeqLM.from_pretrained("google/bert2bert_L-24_wmt_de_en")
-
-sentence = "Willst du einen Kaffee trinken gehen mit mir?"
-
-input_ids = tokenizer(sentence, return_tensors="pt", add_special_tokens=False).input_ids
-output_ids = model.generate(input_ids)[0]
-print(tokenizer.decode(output_ids, skip_special_tokens=True))
-# should output
-# Want to drink a kaffee go with me? .
-```

model_cards/google/bert2bert_L-24_wmt_en_de/README.md

----
-language: 
-- en
-- de
-license: apache-2.0
-datasets:
-- wmt14
-tags:
-- translation
----
-
-# bert2bert_L-24_wmt_en_de EncoderDecoder model
-
-The model was introduced in 
-[this paper](https://arxiv.org/abs/1907.12461) by Sascha Rothe, Shashi Narayan, Aliaksei Severyn and first released in [this repository](https://tfhub.dev/google/bertseq2seq/bert24_en_de/1). 
-
-The model is an encoder-decoder model that was initialized on the `bert-large` checkpoints for both the encoder 
-and decoder and fine-tuned on English to German translation on the WMT dataset, which is linked above.
-
-Disclaimer: The model card has been written by the Hugging Face team.
-
-## How to use
-
-You can use this model for translation, *e.g.*
-
-```python
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
-
-tokenizer = AutoTokenizer.from_pretrained("google/bert2bert_L-24_wmt_en_de", pad_token="<pad>", eos_token="</s>", bos_token="<s>")
-model = AutoModelForSeq2SeqLM.from_pretrained("google/bert2bert_L-24_wmt_en_de")
-
-sentence = "Would you like to grab a coffee with me this week?"
-
-input_ids = tokenizer(sentence, return_tensors="pt", add_special_tokens=False).input_ids
-output_ids = model.generate(input_ids)[0]
-print(tokenizer.decode(output_ids, skip_special_tokens=True))
-# should output
-# Möchten Sie diese Woche einen Kaffee mit mir schnappen?

model_cards/google/bert_uncased_L-10_H-128_A-2/README.md

-../../iuliaturc/bert_uncased_L-2_H-128_A-2/README.md
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model_cards/google/bert_uncased_L-10_H-256_A-4/README.md

-../../iuliaturc/bert_uncased_L-2_H-128_A-2/README.md
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model_cards/google/bert_uncased_L-10_H-512_A-8/README.md

-../../iuliaturc/bert_uncased_L-2_H-128_A-2/README.md
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model_cards/google/bert_uncased_L-10_H-768_A-12/README.md

-../../iuliaturc/bert_uncased_L-2_H-128_A-2/README.md
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model_cards/google/bert_uncased_L-12_H-128_A-2/README.md

-../../iuliaturc/bert_uncased_L-2_H-128_A-2/README.md
\ No newline at end of file

model_cards/google/bert_uncased_L-12_H-256_A-4/README.md

-../../iuliaturc/bert_uncased_L-2_H-128_A-2/README.md
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model_cards/google/bert_uncased_L-12_H-512_A-8/README.md

-../../iuliaturc/bert_uncased_L-2_H-128_A-2/README.md
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model_cards/google/bert_uncased_L-12_H-768_A-12/README.md

-../../iuliaturc/bert_uncased_L-2_H-128_A-2/README.md
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model_cards/google/bert_uncased_L-2_H-128_A-2/README.md

-../../iuliaturc/bert_uncased_L-2_H-128_A-2/README.md
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model_cards/google/bert_uncased_L-2_H-256_A-4/README.md

-../../iuliaturc/bert_uncased_L-2_H-128_A-2/README.md
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model_cards/google/bert_uncased_L-2_H-512_A-8/README.md

-../../iuliaturc/bert_uncased_L-2_H-128_A-2/README.md
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model_cards/google/bert_uncased_L-2_H-768_A-12/README.md

-../../iuliaturc/bert_uncased_L-2_H-128_A-2/README.md
\ No newline at end of file

model_cards/google/bert_uncased_L-4_H-128_A-2/README.md

-../../iuliaturc/bert_uncased_L-2_H-128_A-2/README.md
\ No newline at end of file

model_cards/google/bert_uncased_L-4_H-256_A-4/README.md

-../../iuliaturc/bert_uncased_L-2_H-128_A-2/README.md
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model_cards/google/bert_uncased_L-4_H-512_A-8/README.md

-../../iuliaturc/bert_uncased_L-2_H-128_A-2/README.md
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model_cards/google/bert_uncased_L-4_H-768_A-12/README.md

-../../iuliaturc/bert_uncased_L-2_H-128_A-2/README.md
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model_cards/google/bert_uncased_L-6_H-128_A-2/README.md

-../../iuliaturc/bert_uncased_L-2_H-128_A-2/README.md
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model_cards/google/bert_uncased_L-6_H-256_A-4/README.md

-../../iuliaturc/bert_uncased_L-2_H-128_A-2/README.md
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