      if seed is not None:
          msg.info(f"Fixing random seed: {seed}")
          fix_random_seed(seed)
  
      component = dot_to_object(config, section)
      if hasattr(component, "model"):
          model = component.model
      else:
          msg.fail(
              f"The section '{section}' does not specify an object that holds a Model.",
 
</s> remove             f"The section '{section}' does not specify an object that holds a Model.",
 </s> add             f"The component '{pipe_name}' does not specify an object that holds a Model.", </s> remove     seed = config["pretraining"]["seed"]
 </s> add     seed = config.get("training", {}).get("seed", None) </s> remove             _, config = util.load_model_from_config(cfg, overrides=config_overrides)
 </s> add             nlp, config = util.load_model_from_config(cfg, overrides=config_overrides) </s> remove     section: str = Arg(..., help="Section that defines the model to be analysed"),
 </s> add     pipe_name: str = Arg(..., help="Name of the pipe of which the model should be analysed"),
    component = nlp.get_pipe(pipe_name)
      if seed is not None:
          msg.info(f"Fixing random seed: {seed}")
          fix_random_seed(seed)
  
    component = nlp.get_pipe(pipe_name)
      if hasattr(component, "model"):
          model = component.model
      else:
          msg.fail(
              f"The section '{section}' does not specify an object that holds a Model.",
keep keep keep keep replace keep keep keep keep keep
 pipe_name instead of section in debug_model 
spacy/cli/debug_model.py