Update README.md

README.md

@@ -32,10 +32,58 @@ I want to stop smoking during driving bicycle .	23:29	A <gerund> does not normal
 
 ```
 
+Grammar termins are highlighted with '< ... >' marks and word examples - with '<< ... >>'
+
 ### Data preprocessing
 
-We lowercased the text and explicitly pointed out the error in the original text
+We lowercased the text, split it from any punctuation, including task specific marks (<< >>) and explicitly pointed out the error in the original text using << >>.
+
+```
+the smoke < < flow > > < < my > > face .	10:17 When the < verb > < < flow > > is used as an < intransitive verb > to express '' to move in a stream '', a < preposition > needs to be placed to indicate the direction. ' to ' and ' towards ' are < prepositions > that indicate direction .
 
+i want to stop smoking < < during > > driving bicycle .	23:29	a < gerund > does not normally follow the < preposition > < < during > > . think of an expression using the < conjunction > ' while ' instead of a < preposition > .
+```
 
 
-## How to use
+## How to use
+
+```python
+
+from transformers import T5ForConditionalGeneration, AutoTokenizer, PreTrainedTokenizerFast
+
+text_with_error = 'I want to stop smoking during driving bicycle .'
+error_span = '23:29'
+
+off1, off2 = list(map(int,error_span.split(":")))
+text_with_error_pointed = text_with_error [:off1] + "< < " + re.sub("\s+", " > > < < ", text_with_error [off1:off2].strip()) + " > > " + text_with_error[off2:]
+text_with_error_pointed = re.sub("\s+", " ", text_with_error_pointed .strip()).lower()
+
+tokenizer = AutoTokenizer.from_pretrained("SkolkovoInstitute/GenChal_2022_nigula")
+model = T5ForConditionalGeneration.from_pretrained("SkolkovoInstitute/GenChal_2022_nigula").cuda();
+model.eval();
+
+def paraphrase(text, model, temperature=1.0, beams=3):
+    texts = [text] if isinstance(text, str) else text
+    inputs = tokenizer(texts, return_tensors='pt', padding=True)['input_ids'].to(model.device)
+    result = model.generate(
+        inputs, 
+#         num_return_sequences=n or 1, 
+        do_sample=False, 
+        temperature=temperature, 
+        repetition_penalty=1.1, 
+        max_length=int(inputs.shape[1] * 3) ,
+#         bad_words_ids=[[2]],  # unk
+        num_beams=beams,
+    )
+    texts = [tokenizer.decode(r, skip_special_tokens=True) for r in result]
+    if isinstance(text, str):
+        return texts[0]
+    return texts
+    
+    
+ paraphrase([pointed_example], model)
+ 
+ # expected output: ["a  gerund > does not normally follow the  preposition >   during > >. think of an expression using the  conjunction >'while'instead of a  preposition >."]
+
+
+```