Update model references to Qwen2.5-VL-7B-Instruct

app.py

@@ -49,12 +49,12 @@ def array_to_image_path(image_array):
     return full_path
     
 models = {
-    "Qwen2.5-VL-7B-Instruct": Qwen2_5_VLForConditionalGeneration.from_pretrained("Qwen2.5-VL-7B-Instruct", trust_remote_code=True, torch_dtype="auto").cuda().eval()
+    "Qwen/Qwen2.5-VL-7B-Instruct": Qwen2_5_VLForConditionalGeneration.from_pretrained("Qwen/Qwen2.5-VL-7B-Instruct", trust_remote_code=True, torch_dtype="auto").cuda().eval()
 
 }
 
 processors = {
-    "Qwen2.5-VL-7B-Instruct": AutoProcessor.from_pretrained("Qwen2.5-VL-7B-Instruct", trust_remote_code=True)
+    "Qwen/Qwen2.5-VL-7B-Instruct": AutoProcessor.from_pretrained("Qwen/Qwen2.5-VL-7B-Instruct", trust_remote_code=True)
 }
 
 DESCRIPTION = "This demo uses[Qwen2.5-VL-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-7B-Instruct)"
@@ -67,7 +67,7 @@ assistant_prompt = '<|assistant|>\n'
 prompt_suffix = "<|end|>\n"
 
 @spaces.GPU
-def run_example(image, model_id="Qwen/Qwen2-VL-7B-Instruct", run_ner=False, ner_labels=DEFAULT_NER_LABELS):
+def run_example(image, model_id="Qwen/Qwen2.5-VL-7B-Instruct", run_ner=False, ner_labels=DEFAULT_NER_LABELS):
     # First get the OCR text
     text_input = "Convert the image to text."
     image_path = array_to_image_path(image)
@@ -235,7 +235,7 @@ with gr.Blocks(css=css) as demo:
         with gr.Row():
             with gr.Column(elem_classes="input-container"):
                 input_img = gr.Image(label="Input Picture", elem_classes="gr-image-input")
-                model_selector = gr.Dropdown(choices=list(models.keys()), label="Model", value="Qwen/Qwen2-VL-7B-Instruct", elem_classes="gr-dropdown")
+                model_selector = gr.Dropdown(choices=list(models.keys()), label="Model", value="Qwen/Qwen2.5-VL-7B-Instruct", elem_classes="gr-dropdown")
                 
                 # Add NER controls
                 with gr.Row():