try even easier way to use trocr

app.py

@@ -1,19 +1,4 @@
 import gradio as gr
-from transformers import TrOCRProcessor, VisionEncoderDecoderModel
-from PIL import Image
 
-# Load model and processor
-processor = TrOCRProcessor.from_pretrained('microsoft/trocr-small-handwritten')
-model = VisionEncoderDecoderModel.from_pretrained('microsoft/trocr-small-handwritten')
-
-# Define the prediction function
-def ocr(image):
-    pixel_values = processor(images=image, return_tensors="pt").pixel_values
-    generated_ids = model.generate(pixel_values)
-    generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
-    return generated_text
-
-# Create a Gradio interface
-demo = gr.Interface(fn=ocr, inputs="image", outputs="text")
-demo.launch()
+gr.load("models/microsoft/trocr-small-handwritten").launch()