GH-2689: Documentation and printout changes for release

README.md

@@ -22,13 +22,9 @@ document embeddings, including our proposed **[Flair embeddings](https://www.acl
 * **A PyTorch NLP framework.** Our framework builds directly on [PyTorch](https://pytorch.org/), making it easy to
 train your own models and experiment with new approaches using Flair embeddings and classes.
 
-Now at [version 0.10](https://github.com/flairNLP/flair/releases)!
+Now at [version 0.11](https://github.com/flairNLP/flair/releases)!
 
 
-## Join Us: Open Positions at HU-Berlin!
-
-If you're interested in doing NLP/ML research to pursue a PhD and love open source, consider applying to [open positions](https://github.com/flairNLP/flair/issues/2446) for research associates and PhD candidates at Humboldt University Berlin! We currently have **three open positions** with application deadlines soon!
-
 ## State-of-the-Art Models
 
 Flair ships with state-of-the-art models for a range of NLP tasks. For instance, check out our latest NER models: 
@@ -79,22 +75,24 @@ tagger.predict(sentence)
 Done! The `Sentence` now has entity annotations. Print the sentence to see what the tagger found.
 
 ```python
+# print the sentence with all annotations
 print(sentence)
+
 print('The following NER tags are found:')
 
-# iterate over entities and print
+# iterate over entities and print each
 for entity in sentence.get_spans('ner'):
     print(entity)
 ```
 
 This should print:
 
 ```console
-Sentence: "I love Berlin ." - 4 Tokens
+Sentence: "I love Berlin ." → ["Berlin"/LOC]
 
 The following NER tags are found:
 
-Span [3]: "Berlin"   [− Labels: LOC (0.9992)]
+Span[2:3]: "Berlin" → LOC (0.999)
 ```
 
 ## Tutorials

flair/__init__.py

@@ -14,6 +14,11 @@
 else:
     device = torch.device("cpu")
 
+# global variable: version
+__version__ = "0.11"
+
+# global variable: arrow symbol
+_arrow = " → "
 
 from . import (  # noqa: E402 import after setting device
     data,
@@ -23,8 +28,6 @@
     visual,
 )
 
-__version__ = "0.10"
-
 logging.config.dictConfig(
     {
         "version": 1,
@@ -60,4 +63,5 @@ def set_seed(seed: int):
     "nn",
     "trainers",
     "visual",
+    "datasets",
 ]