def METHOD_NAME(self):
    adapter_spec = AdapterSpec(
        method=ADAPT_LANGUAGE_MODELING,
        input_prefix="",
        model="openai/davinci",
        output_prefix="",
        max_tokens=0,
    )
    adapter = AdapterFactory.get_adapter(adapter_spec, self.tokenizer_service)
    # The tokens translate to: '�Excuse me�'
    conditioning_tokens: List[TokenizationToken] = [TokenizationToken(110), TokenizationToken(40127)]
    pred_tokens: List[TokenizationToken] = [TokenizationToken(1904), TokenizationToken(502), TokenizationToken(447)]
    prompt, num_conditioning_tokens = adapter.construct_language_modeling_prompt(
        conditioning_tokens=conditioning_tokens, pred_tokens=pred_tokens, max_req_len=5, text=""
    )
    # Ensure the prompt is correct
    assert prompt == "Excuse me"
    # Ensure the number of conditioning tokens is correct
    assert num_conditioning_tokens == 1