Revert to Qwen2.5-VL-7B-Instruct

app.py

@@ -7,7 +7,7 @@ AI image quality assessment using:
 - Multi-image comparison
 - Technical metrics (sharpness, colorfulness, contrast, CLIP)
 
-Powered by Qwen3-VL-8B
+Powered by Qwen2.5-VL-7B
 """
 
 import gradio as gr
@@ -892,7 +892,7 @@ with gr.Blocks(title="Image Evaluator", css=DARK_CSS, theme=gr.themes.Base()) as
     <div style="text-align: center; padding: 20px 0 30px 0;">
         <h1 style="color: #fafafa; font-size: 2.2em; font-weight: 700; margin: 0;">Image Evaluator</h1>
         <p style="color: #71717a; font-size: 1em; margin-top: 8px;">
-            AI image quality assessment powered by <span style="color: #3b82f6;">Qwen3-VL-8B</span>
+            AI image quality assessment powered by <span style="color: #3b82f6;">Qwen2.5-VL-7B</span>
         </p>
     </div>
     ''')
@@ -1035,7 +1035,7 @@ with gr.Blocks(title="Image Evaluator", css=DARK_CSS, theme=gr.themes.Base()) as
 
     gr.HTML('''
     <div style="text-align: center; padding: 30px 0 20px 0; color: #52525b; font-size: 0.85em;">
-        Powered by Qwen3-VL-8B &nbsp;|&nbsp; Soft-TIFA &nbsp;|&nbsp; CLIP &nbsp;|&nbsp; LPIPS
+        Powered by Qwen2.5-VL-7B &nbsp;|&nbsp; Soft-TIFA &nbsp;|&nbsp; CLIP &nbsp;|&nbsp; LPIPS
     </div>
     ''')
 

evaluator.py

@@ -204,8 +204,8 @@ class ImageEvaluator:
 
         self.device = device if torch.cuda.is_available() else "cpu"
 
-        # Load Qwen3-VL-8B-Instruct
-        model_name = "Qwen/Qwen3-VL-8B-Instruct"
+        # Load Qwen2.5-VL-7B-Instruct
+        model_name = "Qwen/Qwen2.5-VL-7B-Instruct"
 
         self.vlm_model = AutoModelForImageTextToText.from_pretrained(
             model_name,
@@ -877,8 +877,8 @@ class EditEvaluator:
 
         self.device = device if torch.cuda.is_available() else "cpu"
 
-        # Load Qwen3-VL-8B-Instruct
-        model_name = "Qwen/Qwen3-VL-8B-Instruct"
+        # Load Qwen2.5-VL-7B-Instruct
+        model_name = "Qwen/Qwen2.5-VL-7B-Instruct"
 
         self.vlm_model = AutoModelForImageTextToText.from_pretrained(
             model_name,