readme: ### How to use
  Here is how to use this model in PyTorch:
  ```python
  from transformers import T5Tokenizer, T5ForConditionalGeneration
  
  model = T5ForConditionalGeneration.from_pretrained("addy88/T5-23-emotions-detections")
  
  tokenizer = T5Tokenizer.from_pretrained("addy88/T5-23-emotions-detections")
  
  text_to_summarize="emotion: i don't like it this is nonsense."
  
  input_ids = tokenizer.encode(text_to_summarize, return_tensors="pt", add_special_tokens=True)
           
           
  input_ids = input_ids.to(self.device)
  
  generated_ids = model.generate(
       input_ids=input_ids,
       num_beams=2,
       max_length=512,
       repetition_penalty=2.5,
       length_penalty=1.0,
       early_stopping=True,
       top_p=0.95,
       top_k=50,
       num_return_sequences=1,
  )
  
  
  preds = [tokenizer.decode(g,skip_special_tokens=True,clean_up_tokenization_spaces=True,)for g in generated_ids]
  ```