diff --git a/scripts/inference-debug.py b/scripts/inference-debug.py
index 0ef10ed..13b02f4 100644
--- a/scripts/inference-debug.py
+++ b/scripts/inference-debug.py
@@ -59,29 +59,29 @@ def main():
 
 
 
-    # 2.3 DEBUG: USE BOOSTER
-    # 2.3. initialize ColossalAI booster
-    if cfg.plugin == "zero2":
-        plugin = LowLevelZeroPlugin(
-            stage=2,
-            precision=cfg.dtype,
-            initial_scale=2**16,
-            max_norm=cfg.grad_clip,
-        )
-        set_data_parallel_group(dist.group.WORLD)
-    elif cfg.plugin == "zero2-seq":
-        plugin = ZeroSeqParallelPlugin(
-            sp_size=cfg.sp_size,
-            stage=2,
-            precision=cfg.dtype,
-            initial_scale=2**16,
-            max_norm=cfg.grad_clip,
-        )
-        set_sequence_parallel_group(plugin.sp_group)
-        set_data_parallel_group(plugin.dp_group)
-    else:
-        raise ValueError(f"Unknown plugin {cfg.plugin}")
-    booster = Booster(plugin=plugin)
+    # # 2.3 DEBUG: USE BOOSTER
+    # # 2.3. initialize ColossalAI booster
+    # if cfg.plugin == "zero2":
+    #     plugin = LowLevelZeroPlugin(
+    #         stage=2,
+    #         precision=cfg.dtype,
+    #         initial_scale=2**16,
+    #         max_norm=cfg.grad_clip,
+    #     )
+    #     set_data_parallel_group(dist.group.WORLD)
+    # elif cfg.plugin == "zero2-seq":
+    #     plugin = ZeroSeqParallelPlugin(
+    #         sp_size=cfg.sp_size,
+    #         stage=2,
+    #         precision=cfg.dtype,
+    #         initial_scale=2**16,
+    #         max_norm=cfg.grad_clip,
+    #     )
+    #     set_sequence_parallel_group(plugin.sp_group)
+    #     set_data_parallel_group(plugin.dp_group)
+    # else:
+    #     raise ValueError(f"Unknown plugin {cfg.plugin}")
+    # booster = Booster(plugin=plugin)
 
 
     # ======================================================
@@ -154,15 +154,15 @@ def main():
     os.makedirs(save_dir, exist_ok=True)
 
 
-    ###  TODO: DEBUG, USE booster
-    torch.set_default_dtype(dtype)
-    # vae, optimizer, _, dataloader, lr_scheduler = booster.boost(
-    #     model=vae, optimizer=optimizer, lr_scheduler=lr_scheduler, dataloader=dataloader
+    # ###  TODO: DEBUG, USE booster
+    # torch.set_default_dtype(dtype)
+    # # vae, optimizer, _, dataloader, lr_scheduler = booster.boost(
+    # #     model=vae, optimizer=optimizer, lr_scheduler=lr_scheduler, dataloader=dataloader
+    # # )
+    # vae, _, _, dataloader, _ = booster.boost(
+    #     model=vae, dataloader=dataloader
     # )
-    vae, _, _, dataloader, _ = booster.boost(
-        model=vae, dataloader=dataloader
-    )
-    torch.set_default_dtype(torch.float)
+    # torch.set_default_dtype(torch.float)
 
 
     # load model using booster