Update readme

README.md

@@ -4,6 +4,7 @@ tags:
 - token-classification
 language:
 - grc
+license: mit
 model-index:
 - name: grc_odycy_joint_sm
   results:
@@ -57,6 +58,27 @@ model-index:
       type: f_score
       value: 0.7130820399
 ---
+
+<p align="center">
+  <img width="200" src="https://github.com/centre-for-humanities-computing/odyCy/raw/main/docs/_static/logo_with_text_below.svg">
+  <div align="center" style="color: #2c5882; font-weight: bold; font-size: 18px; margin-top: -20px;">
+    A general-purpose NLP pipeline for Ancient-Greek.
+  </div>
+</p>
+
+[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/centre-for-humanities-computing/odyCy/blob/main/tutorials/01_odycy_getting_started.ipynb#&offline=true&sandboxMode=true)
+Check out our Documentation on [Basic Usage](https://centre-for-humanities-computing.github.io/odyCy/getting_started.html).
+
+
+## Performance
+
+odyCy achieves state of the art performance on multiple tasks on unseen test data from the Universal Dependencies Perseus treebank,
+and performs second best on the PROIEL treebank’s test set on even more tasks.
+In addition performance also seems relatively stable across the two evaluation datasets in comparison with other NLP pipelines.
+
+For plots and tables on OdyCy's performance, check out the Documentation page on [Performance](https://centre-for-humanities-computing.github.io/odyCy/performance.html)
+
+
 | Feature | Description |
 | --- | --- |
 | **Name** | `grc_odycy_joint_sm` |
@@ -66,8 +88,8 @@ model-index:
 | **Components** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `trainable_lemmatizer`, `frequency_lemmatizer` |
 | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
 | **Sources** | n/a |
-| **License** | n/a |
-| **Author** | [n/a]() |
+| **License** | `MIT` |
+| **Author** | [{Márton Kardos, Jan Kostkan}](https://github.com/centre-for-humanities-computing/odyCy) |
 
 ### Label Scheme