fix: fix checkpoint >6G problem

finetune.py

@@ -25,6 +25,9 @@ from transformers import LlamaForCausalLM, LlamaTokenizer
 
 from utils.prompter import Prompter
 
+from transformers import Seq2SeqTrainer, TrainerCallback, TrainingArguments, TrainerState, TrainerControl
+from transformers.trainer_utils import PREFIX_CHECKPOINT_DIR
+
 
 def train(
     # model/data params
@@ -223,6 +226,21 @@ def train(
         model.is_parallelizable = True
         model.model_parallel = True
 
+    class SavePeftModelCallback(TrainerCallback):
+        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}")
+            kwargs["model"].save_pretrained(checkpoint_folder)
+            pytorch_model_path = os.path.join(checkpoint_folder, "pytorch_model.bin")
+            if os.path.exists(pytorch_model_path):
+                os.remove(pytorch_model_path)
+            return control
+
     trainer = transformers.Trainer(
         model=model,
         train_dataset=train_data,
@@ -251,6 +269,7 @@ def train(
         data_collator=transformers.DataCollatorForSeq2Seq(
             tokenizer, pad_to_multiple_of=8, return_tensors="pt", padding=True
         ),
+        callbacks=[SavePeftModelCallback],
     )
     model.config.use_cache = False