Make it easier to develop without a dev install (#22697)

* Make it easier to develop without a dev install

* Remove ugly hack that doesn't work anyway

docs/source/en/add_new_model.mdx

@@ -202,7 +202,15 @@ source .env/bin/activate
 pip install -e ".[dev]"
 ```
 
-and return to the parent directory
+Depending on your OS, and since the number of optional dependencies of Transformers is growing, you might get a
+failure with this command. If that's the case make sure to install the Deep Learning framework you are working with
+(PyTorch, TensorFlow and/or Flax) then do:
+
+```bash
+pip install -e ".[quality]"
+```
+
+which should be enough for most use cases. You can then return to the parent directory
 
 ```bash
 cd ..

docs/source/en/add_tensorflow_model.mdx

@@ -119,6 +119,13 @@ source .env/bin/activate
 pip install -e ".[dev]"
 ```
 
+Depending on your OS, and since the number of optional dependencies of Transformers is growing, you might get a
+failure with this command. If that's the case make sure to install TensorFlow then do:
+
+```bash
+pip install -e ".[quality]"
+```
+
 **Note:** You don't need to have CUDA installed. Making the new model work on CPU is sufficient.
 
 4. Create a branch with a descriptive name from your main branch

docs/source/en/pr_checks.mdx

@@ -24,7 +24,7 @@ When you open a pull request on 🤗 Transformers, a fair number of checks will
 
 In this document, we will take a stab at explaining what those various checks are and the reason behind them, as well as how to debug them locally if one of them fails on your PR.
 
-Note that they all require you to have a dev install:
+Note that, ideally, they require you to have a dev install:
 
 ```bash
 pip install transformers[dev]
@@ -36,7 +36,18 @@ or for an editable install:
 pip install -e .[dev]
 ```
 
-inside the Transformers repo.
+inside the Transformers repo. Since the number of optional dependencies of Transformers has grown a lot, it's possible you don't manage to get all of them. If the dev install fails, make sure to install the Deep Learning framework you are working with (PyTorch, TensorFlow and/or Flax) then do
+
+```bash
+pip install transformers[quality]
+```
+
+or for an editable install:
+
+```bash
+pip install -e .[quality]
+```
+
 
 ## Tests