Update README.md

README.md

@@ -9,25 +9,26 @@ paust/pko-t5-base model based
 
 Since this model is based on paust/pko-t5-base tokenizer, you need to import it.
 
-from transformers import T5TokenizerFast, T5ForConditionalGeneration
+```from transformers import T5TokenizerFast, T5ForConditionalGeneration
 tokenizer = T5TokenizerFast.from_pretrained("paust/pko-t5-base")
-model = T5ForConditionalGeneration.from_pretrained(emotionanalysis/diaryempathizer-t5-ko)
+model = T5ForConditionalGeneration.from_pretrained(emotionanalysis/diaryempathizer-t5-ko)```
 
+Test code
 
-  import torch
-  from transformers import T5TokenizerFast, T5ForConditionalGeneration
+```import torch
+from transformers import T5TokenizerFast, T5ForConditionalGeneration
 
-  model = T5ForConditionalGeneration.from_pretrained(emotionanalysis/diaryempathizer-t5-ko)
-  device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-  model.to(device)
-  
-  tokenizer = T5TokenizerFast.from_pretrained("paust/pko-t5-base")
-  input_text = """
-  """
-  
-  inputs = tokenizer(input_text, return_tensors="pt", max_length=512, truncation=True, padding="max_length")
-  inputs = {key: value.to(device) for key, value in inputs.items()}
-  outputs = model.generate(input_ids=inputs["input_ids"], max_length=128, num_beams=4, early_stopping=True)
+model = T5ForConditionalGeneration.from_pretrained(emotionanalysis/diaryempathizer-t5-ko)
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model.to(device)
+
+tokenizer = T5TokenizerFast.from_pretrained("paust/pko-t5-base")
+input_text = """
+"""
   
-  generated_comment = tokenizer.decode(outputs[0], skip_special_tokens=True)
-  print(generated_comment)
+inputs = tokenizer(input_text, return_tensors="pt", max_length=512, truncation=True, padding="max_length")
+inputs = {key: value.to(device) for key, value in inputs.items()}
+outputs = model.generate(input_ids=inputs["input_ids"], max_length=128, num_beams=4, early_stopping=True)
+
+generated_comment = tokenizer.decode(outputs[0], skip_special_tokens=True)
+print(generated_comment)```