Fix tokenizer bug

[nanbo-liu]

It looks like pipeline is required to have a tokenizer property.
I added a tokenizer property, even though it's not being used for anything.
Notes that sentence-transformers model has their own tokenizer under property model.

in mlserver-huggingface.common.py::load_pipeline_from_setting function

    # If max_batch_size > 1 we need to ensure tokens are padded
    if settings.max_batch_size > 1:
        model = hf_pipeline.model
        if not hf_pipeline.tokenizer.pad_token_id:
            eos_token_id = model.config.eos_token_id  # type: ignore
            if eos_token_id:
                hf_pipeline.tokenizer.pad_token_id = [str(eos_token_id)]  # type: ignore
            else:
                logger.warning(
                    "Model has neither pad_token or eos_token, setting batch size to 1"
                )
                hf_pipeline._batch_size = 1

We are doing some modification to tokenizer when max_batch_size is greater than 1.
It also seems that inference server would deliberately set max_batch_size to be greater than 1
Sentence-transformer model has their own way to handle max_batch_size.
To avoid bug, we keep a tokenizer property in StEmbeddingPipeline