Update app.py

app.py

@@ -17,12 +17,12 @@ import subprocess
 subprocess.run('pip install flash-attn --no-build-isolation', env={'FLASH_ATTENTION_SKIP_CUDA_BUILD': "TRUE"}, shell=True)
 
 models = {
-    'J-LAB/Florence-Idesire': AutoModelForCausalLM.from_pretrained('J-LAB/Florence-Idesire', trust_remote_code=True).to("cuda").eval(),
+    'J-LAB/Florence_2_B_FluxiAI_Product_Caption': AutoModelForCausalLM.from_pretrained('J-LAB/Florence_2_B_FluxiAI_Product_Caption', trust_remote_code=True).to("cuda").eval(),
     'J-LAB/Florence_2_L_FluxiAI_Product_Caption': AutoModelForCausalLM.from_pretrained('J-LAB/Florence_2_L_FluxiAI_Product_Caption', trust_remote_code=True).to("cuda").eval()
 }
 
 processors = {
-    'J-LAB/Florence-Idesire': AutoProcessor.from_pretrained('J-LAB/Florence-Idesire', trust_remote_code=True),
+    'J-LAB/Florence_2_B_FluxiAI_Product_Caption': AutoProcessor.from_pretrained('J-LAB/Florence_2_B_FluxiAI_Product_Caption', trust_remote_code=True),
     'J-LAB/Florence_2_L_FluxiAI_Product_Caption': AutoProcessor.from_pretrained('J-LAB/Florence_2_L_FluxiAI_Product_Caption', trust_remote_code=True)
 }
 
@@ -117,7 +117,7 @@ def draw_ocr_bboxes(image, prediction):
                   fill=color)
     return image
 
-def process_image(image, task_prompt, text_input=None, model_id='J-LAB/Florence-Idesire'):
+def process_image(image, task_prompt, text_input=None, model_id='J-LAB/Florence_2_B_FluxiAI_Product_Caption'):
     image = Image.fromarray(image)  # Convert NumPy array to PIL Image
     if task_prompt == 'Product Caption':
         task_prompt = '<MORE_DETAILED_CAPTION>'
@@ -151,7 +151,7 @@ with gr.Blocks(css=css) 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='J-LAB/Florence-Idesire')
+                model_selector = gr.Dropdown(choices=list(models.keys()), label="Model", value='J-LAB/Florence_2_B_FluxiAI_Product_Caption')
                 task_type = gr.Radio(choices=['Single task', 'Cascased task'], label='Task type selector', value='Single task')
                 task_prompt = gr.Dropdown(choices=single_task_list, label="Task Prompt", value="Caption")
                 text_input = gr.Textbox(label="Text Input (optional)")