Update README.md

README.md

@@ -21,14 +21,14 @@ It achieves the following results on the evaluation set:
 ### Inference Code versions
 
   # Code
-  from transformers import AutoProcessor, AutoModelForCausalLM
-  import matplotlib.pyplot as plt
-  import matplotlib.patches as patches
+    from transformers import AutoProcessor, AutoModelForCausalLM
+    import matplotlib.pyplot as plt
+    import matplotlib.patches as patches
   
-  model = AutoModelForCausalLM.from_pretrained("Musa07/Florence-2-large-FormClassification-ft", trust_remote_code=True, device_map='cuda') # Load the model on GPU if available
-  processor = AutoProcessor.from_pretrained("Musa07/Florence-2-large-FormClassification-ft", trust_remote_code=True)
+    model = AutoModelForCausalLM.from_pretrained("Musa07/Florence-2-large-FormClassification-ft", trust_remote_code=True, device_map='cuda') # Load the model on GPU if available
+    processor = AutoProcessor.from_pretrained("Musa07/Florence-2-large-FormClassification-ft", trust_remote_code=True)
   
-  def run_example(task_prompt, image, max_new_tokens=128):
+    def run_example(task_prompt, image, max_new_tokens=128):
   
       prompt = task_prompt
       inputs = processor(text=prompt, images=image, return_tensors="pt")