Tweak wording + Add badge w/ number of models on the hub (#8914)

* Add badge w/ number of models on the hub

* try to apease @sgugger 😇



* not sure what this `c` was about [ci skip]

* Fix script and move stuff around

* Fix doc styling error
Co-authored-by: Sylvain Gugger <sylvain.gugger@gmail.com>

README.md

@@ -156,6 +156,10 @@ If you'd like to play with the examples, you must [install the library from sour
 
 ## Models architectures
 
+**[All the model checkpoints](https://huggingface.co/models)** provided by 🤗 Transformers are seamlessly integrated from the huggingface.co [model hub](https://huggingface.co) where they are uploaded directly by [users](https://huggingface.co/users) and [organizations](https://huggingface.co/organizations).
+
+Current number of checkpoints: ![](https://img.shields.io/endpoint?url=https://huggingface.co/api/shields/models&color=brightgreen)
+
 🤗 Transformers currently provides the following architectures (see [here](https://huggingface.co/transformers/model_summary.html) for a high-level summary of each them):
 
 1. **[ALBERT](https://huggingface.co/transformers/model_doc/albert.html)** (from Google Research and the Toyota Technological Institute at Chicago) released with the paper [ALBERT: A Lite BERT for Self-supervised Learning of Language Representations](https://arxiv.org/abs/1909.11942), by Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, Radu Soricut.
@@ -195,7 +199,6 @@ ultilingual BERT into [DistilmBERT](https://github.com/huggingface/transformers/
 1. **[XLM-ProphetNet](https://huggingface.co/transformers/model_doc/xlmprophetnet.html)** (from Microsoft Research) released with the paper [ProphetNet: Predicting Future N-gram for Sequence-to-Sequence Pre-training](https://arxiv.org/abs/2001.04063) by Yu Yan, Weizhen Qi, Yeyun Gong, Dayiheng Liu, Nan Duan, Jiusheng Chen, Ruofei Zhang and Ming Zhou.
 1. **[XLM-RoBERTa](https://huggingface.co/transformers/model_doc/xlmroberta.html)** (from Facebook AI), released together with the paper [Unsupervised Cross-lingual Representation Learning at Scale](https://arxiv.org/abs/1911.02116) by Alexis Conneau*, Kartikay Khandelwal*, Naman Goyal, Vishrav Chaudhary, Guillaume Wenzek, Francisco Guzmán, Edouard Grave, Myle Ott, Luke Zettlemoyer and Veselin Stoyanov.
 1. **[XLNet](https://huggingface.co/transformers/model_doc/xlnet.html)** (from Google/CMU) released with the paper [​XLNet: Generalized Autoregressive Pretraining for Language Understanding](https://arxiv.org/abs/1906.08237) by Zhilin Yang*, Zihang Dai*, Yiming Yang, Jaime Carbonell, Ruslan Salakhutdinov, Quoc V. Le.
-1. **[Other community models](https://huggingface.co/models)**, contributed by the [community](https://huggingface.co/users).
 1. Want to contribute a new model? We have added a **detailed guide and templates** to guide you in the process of adding a new model. You can find them in the [`templates`](./templates) folder of the repository. Be sure to check the [contributing guidelines](./CONTRIBUTING.md) and contact the maintainers or open an issue to collect feedbacks before starting your PR.
 
 To check if each model has an implementation in PyTorch/TensorFlow/Flax or has an associated tokenizer backed by the 🤗 Tokenizers library, refer to [this table](https://huggingface.co/transformers/index.html#bigtable)

docs/source/index.rst

@@ -37,6 +37,14 @@ Choose the right framework for every part of a model's lifetime:
 
 Experimental support for Flax with a few models right now, expected to grow in the coming months.
 
+`All the model checkpoints <https://huggingface.co/models>`__ are seamlessly integrated from the huggingface.co `model
+hub <https://huggingface.co>`__ where they are uploaded directly by `users <https://huggingface.co/users>`__ and
+`organizations <https://huggingface.co/organizations>`__.
+
+Current number of checkpoints: |checkpoints|
+
+.. |checkpoints| image:: https://img.shields.io/endpoint?url=https://huggingface.co/api/shields/models&color=brightgreen
+
 Contents
 -----------------------------------------------------------------------------------------------------------------------
 
@@ -168,8 +176,6 @@ and conversion utilities for the following models:
 34. :doc:`XLNet <model_doc/xlnet>` (from Google/CMU) released with the paper `​XLNet: Generalized Autoregressive
     Pretraining for Language Understanding <https://arxiv.org/abs/1906.08237>`__ by Zhilin Yang*, Zihang Dai*, Yiming
     Yang, Jaime Carbonell, Ruslan Salakhutdinov, Quoc V. Le.
-35. `Other community models <https://huggingface.co/models>`__, contributed by the `community
-    <https://huggingface.co/users>`__.
 
 
 .. _bigtable:

utils/check_copies.py

@@ -16,7 +16,7 @@
 import argparse
 import collections
 import glob
-import importlib
+import importlib.util
 import os
 import re
 import tempfile

utils/style_doc.py

@@ -50,7 +50,7 @@ _re_table = re.compile(r"(\+-+)+\+\s*$")
 # Matches a code block in rst `:: `.
 _re_code_block = re.compile(r"^\s*::\s*$")
 # Matches any block of the form `.. something::` or `.. something:: bla`.
-_re_ignore = re.compile(r"^\s*\.\.\s+(\S+)\s*::\s*\S*\s*$")
+_re_ignore = re.compile(r"^\s*\.\.\s+(.*?)\s*::\s*\S*\s*$")
 # Matches comment introduction in rst.
 _re_comment = re.compile(r"\s*\.\.\s*$")
 # Matches the special tag to ignore some paragraphs.