def METHOD_NAME(self, model_class: str, model_name: str, max_seq_len: int):
    """
    Setup the encoding models for the retriever.
    """
    tokenizer_name = "gpt2"
    # new generation of embedding models (December 2022), we need to specify the full name
    if model_name.endswith("-002"):
        self.query_encoder_model = model_name
        self.doc_encoder_model = model_name
        self.max_seq_len = min(8191, max_seq_len)
        tokenizer_name = MODEL_TO_ENCODING.get(model_name, "cl100k_base")
    else:
        self.query_encoder_model = f"text-search-{model_class}-query-001"
        self.doc_encoder_model = f"text-search-{model_class}-doc-001"
        self.max_seq_len = min(2046, max_seq_len)
    return tokenizer_name