diff --git a/swarms/models/base_multimodal_model.py b/swarms/models/base_multimodal_model.py
index 521844a9..28b21d64 100644
--- a/swarms/models/base_multimodal_model.py
+++ b/swarms/models/base_multimodal_model.py
@@ -84,6 +84,8 @@ class BaseMultiModalModel:
         self.device = device
         self.max_new_tokens = max_new_tokens
         self.retries = retries
+        self.system_prompt = system_prompt
+        self.meta_prompt = meta_prompt
         self.chat_history = []
 
     def __call__(self, task: str, img: str, *args, **kwargs):
@@ -309,3 +311,4 @@ class BaseMultiModalModel:
     def set_max_length(self, max_length):
         """Set max_length"""
         self.max_length = max_length
+
diff --git a/swarms/models/fuyu.py b/swarms/models/fuyu.py
index c1e51199..e6f9b04f 100644
--- a/swarms/models/fuyu.py
+++ b/swarms/models/fuyu.py
@@ -1,7 +1,6 @@
-from io import BytesIO
 
-import requests
 from PIL import Image
+from termcolor import colored
 from transformers import (
     AutoTokenizer,
     FuyuForCausalLM,
@@ -9,25 +8,28 @@ from transformers import (
     FuyuProcessor,
 )
 
+from swarms.models.base_multimodal_model import BaseMultiModalModel
 
-class Fuyu:
+
+class Fuyu(BaseMultiModalModel):
     """
     Fuyu model by Adept
 
-
-    Parameters
-    ----------
-    pretrained_path : str
-        Path to the pretrained model
-    device_map : str
-        Device to use for the model
-    max_new_tokens : int
-        Maximum number of tokens to generate
-
-    Examples
-    --------
-    >>> fuyu = Fuyu()
-    >>> fuyu("Hello, my name is", "path/to/image.png")
+    
+    Args:
+        BaseMultiModalModel (BaseMultiModalModel): [description]
+        pretrained_path (str, optional): [description]. Defaults to "adept/fuyu-8b".
+        device_map (str, optional): [description]. Defaults to "auto".
+        max_new_tokens (int, optional): [description]. Defaults to 500.
+        *args: [description]
+        **kwargs: [description]
+    
+    
+    
+    Examples:
+    >>> from swarms.models import Fuyu
+    >>> model = Fuyu()
+    >>> model.run("Hello, world!", "https://upload.wikimedia.org/wikipedia/commons/8/86/Id%C3%A9fix.JPG")
 
     """
 
@@ -39,6 +41,7 @@ class Fuyu:
         *args,
         **kwargs,
     ):
+        super().__init__(*args, **kwargs)
         self.pretrained_path = pretrained_path
         self.device_map = device_map
         self.max_new_tokens = max_new_tokens
@@ -63,33 +66,50 @@ class Fuyu:
         image_pil = Image.open(img)
         return image_pil
 
-    def __call__(self, text: str, img: str):
-        """Call the model with text and img paths"""
-        img = self.get_img(img)
-        model_inputs = self.processor(
-            text=text, images=[img], device=self.device_map
-        )
+    def run(self, text: str, img: str, *args, **kwargs):
+        """Run the pipeline
 
-        for k, v in model_inputs.items():
-            model_inputs[k] = v.to(self.device_map)
-
-        output = self.model.generate(
-            **model_inputs, max_new_tokens=self.max_new_tokens
-        )
-        text = self.processor.batch_decode(
-            output[:, -7:], skip_special_tokens=True
-        )
-        return print(str(text))
+        Args:
+            text (str): _description_
+            img (str): _description_
 
-    def get_img_from_web(self, img: str):
-        """Get the image from the web"""
+        Returns:
+            _type_: _description_
+        """
         try:
-            response = requests.get(img)
-            response.raise_for_status()
-            image_pil = Image.open(BytesIO(response.content))
-            return image_pil
-        except requests.RequestException as error:
-            print(
-                f"Error fetching image from {img} and error: {error}"
+            img = self.get_img(img)
+            model_inputs = self.processor(
+                text=text,
+                images=[img],
+                device=self.device_map,
+                *args,
+                **kwargs,
+            )
+
+            for k, v in model_inputs.items():
+                model_inputs[k] = v.to(self.device_map)
+
+            output = self.model.generate(
+                max_new_tokens=self.max_new_tokens,
+                *args,
+                **model_inputs,
+                **kwargs,
+            )
+            text = self.processor.batch_decode(
+                output[:, -7:],
+                skip_special_tokens=True,
+                *args,
+                **kwargs,
             )
-            return None
+            return print(str(text))
+        except Exception as error:
+            print(
+                colored(
+                    (
+                        "Error in"
+                        f" {self.__class__.__name__} pipeline:"
+                        f" {error}"
+                    ),
+                    "red",
+                )
+            )
\ No newline at end of file
diff --git a/swarms/models/idefics.py b/swarms/models/idefics.py
index d00a1255..70a16622 100644
--- a/swarms/models/idefics.py
+++ b/swarms/models/idefics.py
@@ -79,7 +79,7 @@ class Idefics(BaseMultiModalModel):
             str
         ] = "HuggingFaceM4/idefics-9b-instruct",
         device: Callable = autodetect_device,
-        torch_dtype = torch.bfloat16,
+        torch_dtype=torch.bfloat16,
         max_length: int = 100,
         batched_mode: bool = True,
         *args,
diff --git a/swarms/utils/torch_utils.py b/swarms/utils/torch_utils.py
index 73cf90e1..41d2eb3f 100644
--- a/swarms/utils/torch_utils.py
+++ b/swarms/utils/torch_utils.py
@@ -1,4 +1,4 @@
-import torch 
+import torch
 
 
 def autodetect_device():