---
license: mit
base_model:
- paust/pko-t5-base
pipeline_tag: text2text-generation
---

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
tokenizer = T5TokenizerFast.from_pretrained("paust/pko-t5-base")
model = T5ForConditionalGeneration.from_pretrained(emotionanalysis/diaryempathizer-t5-ko)


  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)
  
  generated_comment = tokenizer.decode(outputs[0], skip_special_tokens=True)
  print(generated_comment)