Update README.md

README.md

@@ -87,7 +87,7 @@ def is_subset(text1, text2):
 def cleaning(text, tags):
     return [tag for tag in tags if is_subset(text, tag)]
     
-def get_texts(self, text, max_len):
+def get_texts(text, max_len):
     texts = list(filter(lambda x : x != '', text.split('\n\n')))
     lengths = [len(tokenizer.encode(paragraph)) for paragraph in texts]
     output = []
@@ -99,7 +99,7 @@ def get_texts(self, text, max_len):
             output.append(par)
     return output
         
-def get_tags(self, text, generate_kwargs):
+def get_tags(text, generate_kwargs):
     input_text = 'summarize: ' + text.strip().replace('\n', ' ')
     tokenized_text = tokenizer.encode(input_text, return_tensors="pt")
     with torch.no_grad():
@@ -115,7 +115,7 @@ def get_tags(self, text, generate_kwargs):
     
     return list(set(itertools.chain(*output))) 
         
-def tag(self, text, max_len, generate_kwargs):
+def tag(text, max_len, generate_kwargs):
     texts = get_texts(text, max_len)
     all_tags = [get_tags(text, generate_kwargs) for text in texts]
     flatten_tags = itertools.chain(*all_tags)