Add a template for examples and apply it for mlm and plm examples (#8153)

* Add a template for example scripts and apply it to mlm

* Formatting

* Fix test

* Add plm script

* Add a template for example scripts and apply it to mlm

* Formatting

* Fix test

* Add plm script

* Add a template for example scripts and apply it to mlm

* Formatting

* Fix test

* Add plm script

* Styling

templates/adding_a_new_example_script/README.md

@@ -1,15 +1,22 @@
-# How to add a new example script in 🤗Transformers
+# How to add a new example script in 🤗 Transformers
 
-This folder provide a template for adding a new example script implementing a training or inference task with the models in the  🤗Transformers library.
-Add tests!
+This folder provide a template for adding a new example script implementing a training or inference task with the
+models in the 🤗 Transformers library. To use it, you will need to install cookiecutter:
+```
+pip install cookiecutter
+```
+or refer to the installation page of the [cookiecutter documentation](https://cookiecutter.readthedocs.io/).
 
+You can then run the following command inside the `examples` folder of the transformers repo:
+```
+cookiecutter ../templates/adding_a_new_example_script/
+```
+and answer the questions asked, which will generate a new folder where you will find a pre-filled template for your
+example following the best practices we recommend for them.
 
-These folder can be put in a subdirectory under your example's name, like `examples/deebert`.
+Adjust the way the data is preprocessed, the model is loaded or the Trainer is instantiated then when you're happy, add
+a `README.md` in the folder (or complete the existing one if you added a script to an existing folder) telling a user
+how to run your script.
 
-
-Best Practices: 
-- use `Trainer`/`TFTrainer`
-- write an @slow test that checks that your model can train on one batch and get a low loss.
-    - this test should use cuda if it's available. (e.g. by checking `transformers.torch_device`)
-- adding an `eval_xxx.py` script that can evaluate a pretrained checkpoint.  
-- tweet about your new example with a carbon screenshot of how to run it and tag @huggingface
+Make a PR to the 🤗 Transformers repo. Don't forget to tweet about your new example with a carbon screenshot of how to
+run it and tag @huggingface!