Release: Adapters v1.1.0

README.md

@@ -40,6 +40,7 @@ HuggingFace's great documentation on getting started with _Transformers_ can be
 
 To get started with adapters, refer to these locations:
 
+- **[Colab notebook tutorials](https://github.com/Adapter-Hub/adapter-transformers/tree/master/notebooks)**, a series notebooks providing an introduction to all the main concepts of (adapter-)transformers and AdapterHub
 - **https://docs.adapterhub.ml**, our documentation on training and using adapters with _adapter-transformers_
 - **https://adapterhub.ml** to explore available pre-trained adapter modules and share your own adapters
 - **[Examples folder](https://github.com/Adapter-Hub/adapter-transformers/tree/master/examples)** of this repository containing HuggingFace's example training scripts, many adapted for training adapters
@@ -50,18 +51,18 @@ To get started with adapters, refer to these locations:
 If you find this library useful, please cite our paper [AdapterHub: A Framework for Adapting Transformers](https://arxiv.org/abs/2007.07779):
 
 ```
-@article{pfeiffer2020AdapterHub,
+@inproceedings{pfeiffer2020AdapterHub,
     title={AdapterHub: A Framework for Adapting Transformers},
-    author={Jonas Pfeiffer and
-            Andreas R\"uckl\'{e} and
-            Clifton Poth and
-            Aishwarya Kamath and
-            Ivan Vuli\'{c} and
-            Sebastian Ruder and
-            Kyunghyun Cho and
-            Iryna Gurevych},
-    journal={arXiv preprint},
-    year={2020},
-    url={https://arxiv.org/abs/2007.07779}
+    author={Pfeiffer, Jonas and
+            R{\"u}ckl{\'e}, Andreas and
+            Poth, Clifton and
+            Kamath, Aishwarya and
+            Vuli{\'c}, Ivan and
+            Ruder, Sebastian and
+            Cho, Kyunghyun and
+            Gurevych, Iryna},
+    booktitle={Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations},
+    pages={46--54},
+    year={2020}
 }
 ```

setup.py

@@ -116,7 +116,7 @@
 
 setup(
     name="adapter-transformers",
-    version="1.0.1",
+    version="1.1.0",
     author="Jonas Pfeiffer, Andreas Rücklé, Clifton Poth, based on work by Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Sam Shleifer, Patrick von Platen, Google AI Language Team Authors, Open AI team Authors, Facebook AI Authors, Carnegie Mellon University Authors",
     author_email="[email protected]",
     description="A friendly fork of Huggingface's Transformers, adding Adapters to PyTorch language models",

src/transformers/__init__.py

@@ -2,7 +2,7 @@
 # There's no way to ignore "F401 '...' imported but unused" warnings in this
 # module, but to preserve other warnings. So, don't check this module at all.
 
-__version__ = "1.0.1"
+__version__ = "1.1.0"
 
 # Work around to update TensorFlow's absl.logging threshold which alters the
 # default Python logging output behavior when present.