Update README.md

README.md

@@ -14,7 +14,7 @@ metric:
 # 🔑 Keyphrase Extraction model: KBIR-inspec
 Keyphrase extraction is a technique in text analysis where you extract the important keyphrases from a text. Since this is a time-consuming process, Artificial Intelligence is used to automate it.
 Currently, classical machine learning methods, that use statistics and linguistics, are widely used for the extraction process. The fact that these methods have been widely used in the community has the advantage that there are many easy-to-use libraries. 
-Now with the recent innovations in deep learning methods (such as recurrent neural networks and transformers, GANS, …), keyword extraction can be improved. These new methods also focus on the semantics and context of a document, which is quite an improvement.
+Now with the recent innovations in deep learning methods (such as recurrent neural networks and transformers, GANS, …), keyphrase extraction can be improved. These new methods also focus on the semantics and context of a document, which is quite an improvement.
 
 
 ## 📓 Model Description
@@ -26,9 +26,9 @@ Paper: https://arxiv.org/abs/2112.08547
 ### ❓ How to use
 ```python
 # Define post_process functions
-def concat_tokens_by_tag(keywords):
+def concat_tokens_by_tag(keyphrases):
     keyphrase_tokens = []
-    for id, label in keywords:
+    for id, label in keyphrases:
         if label == "B":
             keyphrase_tokens.append([id])
         elif label == "I":
@@ -65,13 +65,13 @@ model = AutoModelForTokenClassification.from_pretrained(model_name)
 ```python
 # Inference
 text = """
-Keyword extraction is a technique in text analysis where you extract the important keywords 
+Keyphrase extraction is a technique in text analysis where you extract the important keyphrases 
 from a text. Since this is a time-consuming process, Artificial Intelligence is used to automate it. 
 Currently, classical machine learning methods, that use statistics and linguistics, are widely used 
 for the extraction process. The fact that these methods have been widely used in the community has 
 the advantage that there are many easy-to-use libraries. Now with the recent innovations in 
 deep learning methods (such as recurrent neural networks and transformers, GANS, …), 
-keyword extraction can be improved. These new methods also focus on the semantics 
+keyphrase extraction can be improved. These new methods also focus on the semantics 
 and context of a document, which is quite an improvement.
 """.replace("\n", "")
 
@@ -98,19 +98,19 @@ print(extracted_kps)
 
 ```
 ***** Input Document *****
-Keyword extraction is a technique in text analysis where you extract the important keywords 
+Keyphrase extraction is a technique in text analysis where you extract the important keyphrases 
 from a text. Since this is a time-consuming process, Artificial Intelligence is used to automate it. 
 Currently, classical machine learning methods, that use statistics and linguistics, are widely used 
 for the extraction process. The fact that these methods have been widely used in the community has 
 the advantage that there are many easy-to-use libraries. Now with the recent innovations in 
 deep learning methods (such as recurrent neural networks and transformers, GANS, …), 
-keyword extraction can be improved. These new methods also focus on the semantics 
+keyphrase extraction can be improved. These new methods also focus on the semantics 
 and context of a document, which is quite an improvement.
 
 ***** Prediction *****
-['Artificial Intelligence' 'GANS' 'Keyword extraction'
- 'classical machine learning methods' 'context' 'deep learning methods'
- 'keyword extraction' 'linguistics' 'recurrent neural networks'
+['Artificial Intelligence' 'GANS' 'Keyphrase extraction'
+ 'classical machine learning' 'deep learning methods'
+ 'keyphrase extraction' 'linguistics' 'recurrent neural networks'
  'semantics' 'statistics' 'text analysis' 'transformers']
 ```