fix docs

Signed-off-by: Tim Schopf <tim.schopf@t-online.de>

.readthedocs.yaml

@@ -18,7 +18,6 @@ formats: all
 python:
   install:
     - requirements: docs/requirements.txt
-    - requirements: requirements.txt
     - method: pip
       path: .
       extra_requirements:
@@ -27,7 +26,7 @@ python:
 build:
   os: ubuntu-22.04
   tools:
-    python: "3.7"
+    python: "3.8"
 
 submodules:
   include: all

README.md

@@ -127,9 +127,12 @@ vectorizer = KeyphraseCountVectorizer()
 
 # Print parameters
 print(vectorizer.get_params())
+```
+```plaintext
 >>> {'binary': False, 'dtype': <class 'numpy.int64'>, 'lowercase': True, 'max_df': None, 'min_df': None, 'pos_pattern': '<J.*>*<N.*>+', 'spacy_exclude': ['parser', 'attribute_ruler', 'lemmatizer', 'ner'], 'spacy_pipeline': 'en_core_web_sm', 'stop_words': 'english', 'workers': 1}
 ```
 
+
 By default, the vectorizer is initialized for the English language. That means, an English `spacy_pipeline` is
 specified, English `stop_words` are removed, and the `pos_pattern` extracts keywords that have 0 or more adjectives,
 followed by 1 or more nouns using the English spaCy part-of-speech tags. In addition, the spaCy pipeline
@@ -255,14 +258,11 @@ vectorizer = KeyphraseTfidfVectorizer()
 
 # Print parameters
 print(vectorizer.get_params())
->>> {'binary': False, 'custom_pos_tagger': None, 'decay': None, 'delete_min_df': None, 'dtype': <
-
-
-class 'numpy.int64'>, 'lowercase': True, 'max_df': None
-
-, 'min_df': None, 'pos_pattern': '<J.*>*<N.*>+', 'spacy_exclude': ['parser', 'attribute_ruler', 'lemmatizer', 'ner',
-                                                                   'textcat'], 'spacy_pipeline': 'en_core_web_sm', 'stop_words': 'english', 'workers': 1}
 ```
+```plaintext
+>>> {'binary': False, 'custom_pos_tagger': None, 'decay': None, 'delete_min_df': None, 'dtype': <class 'numpy.int64'>, 'lowercase': True, 'max_df': None, 'min_df': None, 'pos_pattern': '<J.*>*<N.*>+', 'spacy_exclude': ['parser', 'attribute_ruler', 'lemmatizer', 'ner','textcat'], 'spacy_pipeline': 'en_core_web_sm', 'stop_words': 'english', 'workers': 1}
+```
+
 
 To calculate tf values instead, set `use_idf=False`.
 

docs/requirements.txt

@@ -14,6 +14,7 @@ docutils>=0.16
 numpy>=1.18.5
 spacy>=3.0.1
 spacy-transformers>=1.1.6
+spacy-curated-transformers>=0.2.2
 nltk>=3.6.1
 scikit-learn>=1.0
 scipy>=1.7.3