class_docstr: Base class for model wrapper.
  
  Args:
      path: The path to the model.
      model_max_length: The maximum sequence length of the model.
      prompt_template: The model's prompt template.
      batch_size: Batch size for inference.
      logger: Logger for the model.
docstr: Infer the given data.
  This function will call self.generate() to get model outputs and also self.model(input) to get logits.
  
  Args:
      data: The data for inference.
code: def inference(self, data: List[Dict]) -> None:
      """
      Infer the given data.
      This function will call self.generate() to get model outputs and also self.model(input) to get logits.
  
      Args:
          data: The data for inference.
      """
  
file_path: ColossalAI/applications/ColossalEval/colossal_eval/models/base.py
imports: from abc import abstractclassmethod
  from typing import Dict, List
  from colossal_eval.utils import Conversation, prompt_templates
  from colossalai.logging import DistributedLogger
label_desc: Use image node_id 2 for calling the BaseModel obj's underlying member method code with example usage: obj.inference(data) without return types