readme: ---
  license: lgpl-3.0
  ---
  
  # t5_interpreter
  
  A rut5-based model for incomplete utterance restoration, spellchecking and text normalization for dialogue utterances.
  
  Read more about the task [here](https://huggingface.co/inkoziev/rugpt_interpreter).
  
  
  # Usage example
  
  ```
  import torch
  from transformers import T5ForConditionalGeneration, T5Tokenizer
  
  model_name = 'inkoziev/t5_interpreter'
  tokenizer = T5Tokenizer.from_pretrained(model_name,)
  device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
  model = T5ForConditionalGeneration.from_pretrained(model_name)
  model.eval()
  
  t5_input = '- Тебя как зовут?\n- Мальвина #'
  input_ids = tokenizer(t5_input, return_tensors='pt').input_ids
  out_ids = model.generate(input_ids=input_ids, max_length=40, eos_token_id=tokenizer.eos_token_id, early_stopping=True)
  t5_output = tokenizer.decode(out_ids[0][1:])
  print(t5_output)
  ```
  
  
  