Update README.md

README.md

@@ -22,7 +22,7 @@ from transformers import AutoTokenizer, AutoModelForTokenClassification
 
 Firstly, you'll have to define this method, since the text preprocessing is custom and the standard `pipeline` method won't suffice:
 ```python
-def get_keywords(
+def extract_keywords(
     text: str, 
     model_id="auhide/keybert-bg", 
     max_len: int = 300,
@@ -85,14 +85,14 @@ def get_keywords(
 ```
 
 Choose a text and use the model on it. For example, I've chosen to use [this](https://novini.bg/biznes/biznes_tehnologii/781108) article.
-Then, you can call `get_keywords` on it and extract its keywords:
+Then, you can call `extract_keywords` on it and extract its keywords:
 ```python
 # Reading the text from a file, since it is an article, and the text is large.
 with open("input_text.txt", "r", encoding="utf-8") as f:
     text = f.read()
 
 # You can change the threshold based on your needs.
-keywords = get_keywords(text, threshold=0.5)
+keywords = extract_keywords(text, threshold=0.5)
 print("Keywords:")
 pprint(keywords)
 ```