def _generate_response_hf(self, prompt: str, num_copies: int = 2) -> List[str]:
        """
        Generate responses from the model based on the provided prompt, duplicated to form a batch.

        Parameters:
        - prompt (str): The input prompt to generate responses for.
        - num_copies (int): The number of copies of the prompt to create for batch processing (default is 16).

        Returns:
        - List[str]: A list of generated responses, each corresponding to a duplicate of the input prompt.
        """
        if self.pipe is None:
            raise ValueError("LLM service not started. Please call start_service() first.")

        # Create a batch of the same prompt
        prompts = [prompt] * num_copies

        # Generate responses from the model
        responses = self.pipe(
            prompts,
            max_new_tokens=self.max_new_tokens,
            batch_size=num_copies,
            do_sample=True,
            temperature=self.temperature,
            top_k=self.top_k,
            top_p=self.top_p,
            return_full_text=False
        )
        response_message_batch = [result[0]["generated_text"] for result in responses]

        # Extract and return the generated text for each response
        return response_message_batch

        Generate responses from the model based on the provided prompt, duplicated to form a batch.

        Parameters:
        - prompt (str): The input prompt to generate responses for.
        - num_copies (int): The number of copies of the prompt to create for batch processing (default is 16).

        Returns:
        - List[str]: A list of generated responses, each corresponding to a duplicate of the input prompt.
        
data/omegaPRM_v2/llm_utils.py