make the pipeline simple

models/blip2_model.py

@@ -14,9 +14,13 @@ class ImageCaptioning:
             self.data_type = torch.float32
         else:
             self.data_type = torch.float16
-        processor = Blip2Processor.from_pretrained("pretrained_models/blip2-opt-2.7b")
+        # processor = Blip2Processor.from_pretrained("pretrained_models/blip2-opt-2.7b")
+        # model = Blip2ForConditionalGeneration.from_pretrained(
+        #     "pretrained_models/blip2-opt-2.7b", torch_dtype=self.data_type
+        # )
+        processor = Blip2Processor.from_pretrained("Salesforce/blip2-opt-2.7b")
         model = Blip2ForConditionalGeneration.from_pretrained(
-            "pretrained_models/blip2-opt-2.7b", torch_dtype=self.data_type
+            "Salesforce/blip2-opt-2.7b", torch_dtype=self.data_type
         )
         model.to(self.device)
         return processor, model

models/controlnet_model.py

@@ -25,7 +25,8 @@ class TextToImage:
             map_location=self.device,  # Add this line
         ).to(self.device)
         pipeline = StableDiffusionControlNetPipeline.from_pretrained(
-            "pretrained_models/stable-diffusion-v1-5",
+            # "pretrained_models/stable-diffusion-v1-5",
+            "runwayml/stable-diffusion-v1-5",
             controlnet=controlnet,
             safety_checker=None,
             torch_dtype=self.data_type,