diff --git a/src/llmtuner/dsets/loader.py b/src/llmtuner/dsets/loader.py
index 08c35f27..3b42f17d 100644
--- a/src/llmtuner/dsets/loader.py
+++ b/src/llmtuner/dsets/loader.py
@@ -65,6 +65,8 @@ def get_dataset(
             max_samples_temp = min(len(dataset), max_samples)
             dataset = dataset.select(range(max_samples_temp))
 
+        # TODO: adapt to the sharegpt format
+
         for column_name in ["prompt", "query", "response", "history"]: # align datasets
             if getattr(dataset_attr, column_name) and getattr(dataset_attr, column_name) != column_name:
                 dataset = dataset.rename_column(getattr(dataset_attr, column_name), column_name)
diff --git a/src/llmtuner/webui/runner.py b/src/llmtuner/webui/runner.py
index 4ea54168..2af4d4a7 100644
--- a/src/llmtuner/webui/runner.py
+++ b/src/llmtuner/webui/runner.py
@@ -138,13 +138,14 @@ class Runner:
             lora_rank=lora_rank,
             lora_dropout=lora_dropout,
             lora_target=lora_target or DEFAULT_MODULE.get(model_name.split("-")[0], "q_proj,v_proj"),
-            resume_lora_training=(
-                False if TRAINING_STAGES[training_stage] in ["rm", "ppo", "dpo"] else resume_lora_training
-            ),
+            resume_lora_training=resume_lora_training,
             output_dir=output_dir
         )
         args[compute_type] = True
 
+        if TRAINING_STAGES[training_stage] in ["rm", "ppo", "dpo"] and args["quantization_bit"] is None:
+            args["resume_lora_training"] = False
+
         if args["quantization_bit"] is not None:
             args["upcast_layernorm"] = True