diff --git a/README.md b/README.md
index cad3676..071bcf6 100644
--- a/README.md
+++ b/README.md
@@ -77,31 +77,32 @@ import requests
 
 from PIL import Image
 from transformers import AutoProcessor, AutoModelForCausalLM 
+from modelscope import snapshot_download
 
+model_dir = snapshot_download("AI-ModelScope/Florence-2-large")
 
-model = AutoModelForCausalLM.from_pretrained("microsoft/Florence-2-large", trust_remote_code=True)
-processor = AutoProcessor.from_pretrained("microsoft/Florence-2-large", trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(model_dir, trust_remote_code=True)
+processor = AutoProcessor.from_pretrained(model_dir, trust_remote_code=True)
 
-url = "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/tasks/car.jpg?download=true"
+prompt = "<OD>"
+
+url = "https://modelscope.oss-cn-beijing.aliyuncs.com/resource/car.jpg"
 image = Image.open(requests.get(url, stream=True).raw)
 
-def run_example(task_prompt, text_input=None):
-    if text_input is None:
-        prompt = task_prompt
-    else:
-        prompt = task_prompt + text_input
-    inputs = processor(text=prompt, images=image, return_tensors="pt")
-    generated_ids = model.generate(
-      input_ids=inputs["input_ids"],
-      pixel_values=inputs["pixel_values"],
-      max_new_tokens=1024,
-      num_beams=3
-    )
-    generated_text = processor.batch_decode(generated_ids, skip_special_tokens=False)[0]
+inputs = processor(text=prompt, images=image, return_tensors="pt")
 
-    parsed_answer = processor.post_process_generation(generated_text, task=task_prompt, image_size=(image.width, image.height))
+generated_ids = model.generate(
+    input_ids=inputs["input_ids"],
+    pixel_values=inputs["pixel_values"],
+    max_new_tokens=1024,
+    num_beams=3,
+    do_sample=False
+)
+generated_text = processor.batch_decode(generated_ids, skip_special_tokens=False)[0]
 
-    print(parsed_answer)
+parsed_answer = processor.post_process_generation(generated_text, task="<OD>", image_size=(image.width, image.height))
+
+print(parsed_answer)
 ```
 </details>