Update README.md

README.md

@@ -30,14 +30,15 @@ tokenizer = M2M100Tokenizer.from_pretrained(model_name)
 model = M2M100ForConditionalGeneration.from_pretrained(model_name)
 
 # Example sentence
-text = "The model was fine-tuned using knowledge distillation techniques."
+text = "The model was fine-tuned using knowledge distillation techniques. The training dataset was created using a collaborative multi-agent framework powered by large language models."
 
 # Tokenize and generate translation
 tokenizer.src_lang = "en"
-encoded = tokenizer(text, return_tensors="pt")
+encoded = tokenizer(text.split('. '), return_tensors="pt", padding=True)
 generated_tokens = model.generate(**encoded, forced_bos_token_id=tokenizer.get_lang_id("ko"))
-tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
-# => "이 모델은 지식 증류 기법(knowledge distillation techniques)을 사용하여 미세 조정되었습니다."
+outputs = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
+print(' '.join(outputs))
+# => "이 모델은 지식 증류 기법(knowledge distillation techniques)을 사용하여 미세 조정되었습니다. 훈련 데이터셋(training dataset)은 대형 언어 모델(large language models)을 기반으로 한 협업 다중 에이전트 프레임워크(collaborative multi-agent framework)를 사용하여 생성되었습니다."
 
 ```