Update app.py

app.py

@@ -40,7 +40,7 @@ def fig_to_pil(fig):
     return Image.open(buf)
 
 @spaces.GPU
-def run_example(task_prompt, image, text_input=None, model_id='dwb2023/florence2-large-bccd-base-ft'):
+def run_example(task_prompt, image, text_input=None, model_id='dwb2023/florence2-large-liver-disease-ft'):
     model = models[model_id]
     processor = processors[model_id]
     if text_input is None:
@@ -118,7 +118,7 @@ def draw_ocr_bboxes(image, prediction):
                   fill=color)
     return image
 
-def process_image(image, task_prompt, text_input=None, model_id='dwb2023/florence2-large-bccd-base-ft'):
+def process_image(image, task_prompt, text_input=None, model_id='dwb2023/florence2-large-liver-disease-ft'):
     image = Image.fromarray(image)  # Convert NumPy array to PIL Image
     if task_prompt == 'Object Detection':
         task_prompt = '<OD>'
@@ -145,7 +145,7 @@ with gr.Blocks(theme="sudeepshouche/minimalist") as demo:
         with gr.Row():
             with gr.Column():
                 input_img = gr.Image(label="Input Picture")
-                model_selector = gr.Dropdown(choices=list(models.keys()), label="Model", value='dwb2023/florence2-large-bccd-base-ft')
+                model_selector = gr.Dropdown(choices=list(models.keys()), label="Model", value='dwb2023/florence2-large-liver-disease-ft')
                 task_prompt = gr.Dropdown(choices=single_task_list, label="Task Prompt", value="Object Detection")
                 text_input = gr.Textbox(label="Text Input", placeholder="Not used for Florence-2 Object Detection")
                 submit_btn = gr.Button(value="Submit")