Yes,
The Parameter would be correct, but the current released transformers only support padding, and truncation as **kwargs if you take a look here:
  

      github.com
  

  
    huggingface/transformers/blob/a5fc34437dc2cfbd9e91f732820304c017b5525d/src/transformers/pipelines/base.py#L742 2



      
      
                      if isinstance(model, tuple):
                          supported_models_names.extend([_model.__name__ for _model in model])
                      else:
                          supported_models_names.append(model.__name__)
                  supported_models = supported_models_names
              if self.model.__class__.__name__ not in supported_models:
                  logger.error(
                      f"The model '{self.model.__class__.__name__}' is not supported for {self.task}. Supported models are {supported_models}."
                  )
          
          
def _parse_and_tokenize(
              self, inputs, padding=True, add_special_tokens=True, truncation=TruncationStrategy.DO_NOT_TRUNCATE, **kwargs
          ):
              """
              Parse arguments and tokenize
              """
              # Parse arguments
              if getattr(self.tokenizer, "pad_token", None) is None:
                  padding = False
              inputs = self.tokenizer(
                  inputs,
      
    
  


  

  
    
    
  

  


But the next transformers version will allow all **tokenizers_kwargs to be passed in.