add issues and requests guidelines

CONTRIBUTING.md

@@ -0,0 +1,86 @@
+# How to contribute to transformers?
+
+Everyone is welcome to contribute, and we value everybody's contribution. Code
+is thus not the only way to contribute. Answering questions, helping others,
+reaching out and improving the documentations are immensely valuable to the
+community.
+
+It also helps us if you spread the word: reference the library from blog posts
+on the awesome projects it made possible, shout out on twitter every time it has
+helped you, or simply star the repo to say "thank you".
+
+## You can contribute in so many ways!
+
+There are 4 ways you can contribute to transformers:
+* Fixing outstanding issues with the existing code;
+* Implementing new models;
+* Contributing to the examples, or to the documentation;
+* Submitting issues related to bugs or desired new features.
+
+*All are equally valuable to the community.*
+
+## Submitting a new issue or feature request
+
+Do your best to follow these guidelines when submitting an issue or a feature
+request. It will make it easier for us to come back to you quickly and with good
+feedback.
+
+### Did you find a bug?
+
+The transformers are robust and reliable thanks to the users who notify us of
+the problems they encounter.
+
+So thank you for reporting an issue. First, we would really appreciate it if you
+could **make sure the bug was not already reported** (use the search bar on
+Github under Issues).
+
+Did not find it? :( So we can act quickly on it, please follow these steps:
+
+* Include your **OS type and version**, the versions of **Python**, **PyTorch** and
+  **Tensorflow** when applicable;
+* A short, self-contained, code snippet that allows us to reproduce the bug in
+  less than 30s.
+* Provide the *full* traceback if an exception is raised.
+
+To get the OS and software versions, execute the following code and copy-paste
+the output:
+
+```
+import platform; print("Platform", platform.platform())
+import sys; print("Python", sys.version)
+import torch; print("PyTorch", torch.__version__)
+import tensorflow; print("Tensorflow", tensorflow.__version__)
+```
+
+### Do you want to implement a new model?
+
+Please provide the following:
+
+* Short description of the model and link to the paper
+* Link to the implementation if open-source
+* Link to the model weights if they are available
+
+Let us know if you are willing to contribute so we can best guide you. 
+
+### Do you want a new feature (that is not a model)?
+
+A world-class feature request addresses the following points:
+
+1. Motivation first:
+  * Is it related to a problem/frustration with the library? If so, please explain
+    why. Providing a code snippet that demonstrates the problem is best.
+  * Is it related to something you would need for a project? We'd love to hear
+    about it!
+  * Is it something you worked on and think could benefit the community?
+    Awesome! Tell us what problem it solved for you.
+2. Write a *full paragraph* describing the feature.  
+3. Provide a **code snippet** that demonstrates its future use.
+4. In case this is related to a paper, please provide a link
+5. Attach any additional information (drawings, screenshots, etc.) you think may help.
+
+If your issue is well-written we're already 80% of the way there by the time you
+post it.
+
+## Contributing code
+
+## Contributing examples