Update app.py

app.py

@@ -15,6 +15,7 @@ import cv2
 
 from transformers import (
     Qwen2_5_VLForConditionalGeneration,
+    Qwen2VLForConditionalGeneration,
     Gemma3ForConditionalGeneration,
     AutoProcessor,
     TextIteratorStreamer,
@@ -38,7 +39,7 @@ model_m = Gemma3ForConditionalGeneration.from_pretrained(
 ).to(device).eval()
 
 # Load DocScope
-MODEL_ID_X = "prithivMLmods/docscopeOCR-7B-050425-exp"
+MODEL_ID_X = "prithivMLmods/coreOCR-7B-050325-preview"
 processor_x = AutoProcessor.from_pretrained(MODEL_ID_X, trust_remote_code=True)
 model_x = Qwen2_5_VLForConditionalGeneration.from_pretrained(
     MODEL_ID_X,
@@ -89,7 +90,7 @@ def generate_image(model_name: str, text: str, image: Image.Image,
     if model_name == "gemma-3-4b-it":
         processor = processor_m
         model = model_m
-    elif model_name == "docscopeOCR-7B-050425-exp":
+    elif model_name == "coreOCR-7B-050325-preview":
         processor = processor_x
         model = model_x
     elif model_name == "Captioner-7B":
@@ -245,7 +246,7 @@ with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
         with gr.Column():
             output = gr.Textbox(label="Output", interactive=False, lines=2, scale=2)
             model_choice = gr.Radio(
-                choices=["gemma-3-4b-it", "docscopeOCR-7B-050425-exp", "Captioner-7B"],
+                choices=["gemma-3-4b-it", "coreOCR-7B-050325-preview", "Captioner-7B"],
                 label="Select Model",
                 value="gemma-3-4b-it"
             )