chore(callback): Remove old peft saving code

src/axolotl/utils/callbacks.py

@@ -43,29 +43,6 @@
 IGNORE_INDEX = -100
 
 
-class SavePeftModelCallback(TrainerCallback):  # pylint: disable=too-few-public-methods
-    """Callback to save the PEFT adapter"""
-
-    def on_save(
-        self,
-        args: TrainingArguments,
-        state: TrainerState,
-        control: TrainerControl,
-        **kwargs,
-    ):
-        checkpoint_folder = os.path.join(
-            args.output_dir,
-            f"{PREFIX_CHECKPOINT_DIR}-{state.global_step}",
-        )
-
-        peft_model_path = os.path.join(checkpoint_folder, "adapter_model")
-        kwargs["model"].save_pretrained(
-            peft_model_path, save_safetensors=args.save_safetensors
-        )
-
-        return control
-
-
 class SaveBetterTransformerModelCallback(
     TrainerCallback
 ):  # pylint: disable=too-few-public-methods

src/axolotl/utils/trainer.py

@@ -30,7 +30,6 @@
 from axolotl.utils.callbacks import (
     GPUStatsCallback,
     SaveBetterTransformerModelCallback,
-    SavePeftModelCallback,
     bench_eval_callback_factory,
     log_prediction_callback_factory,
 )
@@ -708,12 +707,6 @@ def setup_trainer(cfg, train_dataset, eval_dataset, model, tokenizer, total_num_
     if cfg.relora_steps:
         callbacks.append(ReLoRACallback(cfg))
 
-    if cfg.local_rank == 0 and cfg.adapter in [
-        "lora",
-        "qlora",
-    ]:  # only save in rank 0
-        callbacks.append(SavePeftModelCallback)
-
     if hasattr(model, "use_bettertransformer") and model.use_bettertransformer is True:
         callbacks.append(SaveBetterTransformerModelCallback)