Update README.md

README.md

@@ -45,17 +45,17 @@ pipeline_tag: summarization
 >>> prompt_lengths = inputs["input_ids"].shape[1]
 
 >>> with torch.no_grad():
->>> generated_ids = model.generate(
-  input_ids=inputs["input_ids"],
-  attention_mask=inputs["attention_mask"],
-  max_new_tokens=100,
-  no_repeat_ngram_size=3,
-  num_beams=6,
-  min_length = 30,
-  length_penalty = -0.5,
-  early_stopping = True,
-  pad_token_id = tokenizer.pad_token_id,
-  eos_token_id = tokenizer.pad_token_id)
+>>>  generated_ids = model.generate(
+>>>  input_ids=inputs["input_ids"],
+>>>  attention_mask=inputs["attention_mask"],
+>>>  max_new_tokens=100,
+>>>  no_repeat_ngram_size=3,
+>>>  num_beams=6,
+>>>  min_length = 30,
+>>>  length_penalty = -0.5,
+>>>  early_stopping = True,
+>>>  pad_token_id = tokenizer.pad_token_id,
+>>>  eos_token_id = tokenizer.pad_token_id)
 
 >>> decoded_output = tokenizer.decode(generated_ids[0][prompt_length:], skip_special_tokens=True).strip()