diff --git a/interrogators/blip_interrogator.py b/interrogators/blip_interrogator.py
index d4f81c7..3b0010b 100644
--- a/interrogators/blip_interrogator.py
+++ b/interrogators/blip_interrogator.py
@@ -48,7 +48,7 @@ class BLIPInterrogator(Interrogator):
         try:
             model_path = fetch_model('Salesforce/blip2-opt-6.7b', "blip2")
             self.processor = AutoProcessor.from_pretrained(model_path)
-            self.model = Blip2ForConditionalGeneration.from_pretrained(model_path, torch_dtype=torch.float16, load_in_8bit=True)
+            self.model = Blip2ForConditionalGeneration.from_pretrained(model_path, torch_dtype=torch.float16, load_in_8bit=False)
             self.device = "cuda" if torch.cuda.is_available() else "cpu"
             self.model.to(self.device)
         except:
diff --git a/interrogators/llava2_interrogator.py b/interrogators/llava2_interrogator.py
index 30644f8..63823c1 100644
--- a/interrogators/llava2_interrogator.py
+++ b/interrogators/llava2_interrogator.py
@@ -43,7 +43,7 @@ Avoid adding new information not supported by the existing caption or the image.
 class LLAVA2Interrogator(Interrogator):
     model = None
     processor = None
-    params = {"max_tokens": 75, "load_mplug_8bit": True}
+    params = {"max_tokens": 75, "load_mplug_8bit": False}
 
     def __init__(self, params: ProcessParams):
         super().__init__(params)
diff --git a/process_params.py b/process_params.py
index 4625b60..fbab0f4 100644
--- a/process_params.py
+++ b/process_params.py
@@ -25,7 +25,7 @@ class ProcessParams:
     dst: str = ""
     face_model: str = "Codeformers"
     flip: bool = False
-    load_mplug_8bit: bool = True
+    load_mplug_8bit: bool = False
     max_clip_tokens: float = 1.0
     max_size: int = 1024
     max_tokens: int = 75
diff --git a/smartprocess.py b/smartprocess.py
index 5e92934..c366746 100644
--- a/smartprocess.py
+++ b/smartprocess.py
@@ -561,7 +561,6 @@ def process_post(files: ImageData, params: ProcessParams) -> List[ImageData]:
     if params.upscale:
         total_post += total_files
     pbar = tqdm(total=total_post, desc="Post-processing images")
-    params.do_rename = False
     upscalers = []
 
     if params.upscale:
@@ -570,7 +569,7 @@ def process_post(files: ImageData, params: ProcessParams) -> List[ImageData]:
             upscalers.append(params.upscaler_1)
         if params.upscaler_2 is not None and params.upscaler_2 != "None":
             upscalers.append(params.upscaler_2)
-
+    img_index = 0
     for file in files:
         img = file.get_image()
         if params.restore_faces:
@@ -637,10 +636,11 @@ def process_post(files: ImageData, params: ProcessParams) -> List[ImageData]:
                     shared.state.current_image = img
 
         if params.save_image:
-            img_path = save_pic(img, file, 0, params)
+            img_path = save_pic(img, file, img_index, params)
             file.image_path = img_path
         file.update_image(img, False)
         output.append(file)
+        img_index += 1
     return output