      config_overrides = parse_config_overrides(ctx.args)
      cfg = Config().from_disk(config_path)
      with show_validation_error():
          try:
              _, config = util.load_model_from_config(cfg, overrides=config_overrides)
          except ValueError as e:
              msg.fail(str(e), exits=1)
      seed = config["pretraining"]["seed"]
      if seed is not None:
          msg.info(f"Fixing random seed: {seed}")
 
</s> remove     seed = config["pretraining"]["seed"]
 </s> add     seed = config.get("training", {}).get("seed", None) </s> remove     component = dot_to_object(config, section)
 </s> add     component = nlp.get_pipe(pipe_name) </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"), </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.",
            nlp, config = util.load_model_from_config(cfg, overrides=config_overrides)
      config_overrides = parse_config_overrides(ctx.args)
      cfg = Config().from_disk(config_path)
      with show_validation_error():
          try:
            nlp, config = util.load_model_from_config(cfg, overrides=config_overrides)
          except ValueError as e:
              msg.fail(str(e), exits=1)
      seed = config["pretraining"]["seed"]
      if seed is not None:
          msg.info(f"Fixing random seed: {seed}")
keep keep keep keep replace keep keep keep keep keep
 pipe_name instead of section in debug_model 
spacy/cli/debug_model.py