Update app.py

app.py

@@ -1,40 +1,26 @@
+from transformers import AutoProcessor, AutoModelForVision2Seq
 import torch
-import gradio as gr
 from PIL import Image
-from transformers import AutoProcessor, AutoModelForVision2Seq
-import traceback
+import gradio as gr
 
-processor = AutoProcessor.from_pretrained("scb10x/typhoon-ocr-3b")
+processor = AutoProcessor.from_pretrained("scb10x/typhoon-ocr-1b")
 model = AutoModelForVision2Seq.from_pretrained(
-    "scb10x/typhoon-ocr-3b",
+    "scb10x/typhoon-ocr-1b",
     torch_dtype=torch.float16,
     device_map="auto"
 )
-# ❌ ห้ามใส่ model.to(device)
 
 def ocr_infer(image):
     try:
-        if image is None:
-            return "❌ Error: No image provided"
-
         image = image.convert("RGB")
         inputs = processor(images=image, return_tensors="pt")
-        inputs = {k: v.to(model.device) for k, v in inputs.items()}  # ✅ ใช้ model.device
+        inputs = {k: v.to(model.device) for k, v in inputs.items()}
 
         generated_ids = model.generate(**inputs, max_new_tokens=256)
         result = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
         return result
-
     except Exception as e:
-        traceback.print_exc()
-        return f"❌ Error during inference: {e}"
-
-iface = gr.Interface(
-    fn=ocr_infer,
-    inputs=gr.Image(type="pil"),
-    outputs="text",
-    title="Typhoon OCR 3B"
-)
+        return f"❌ Error: {e}"
 
-if __name__ == "__main__":
-    iface.launch()
+iface = gr.Interface(fn=ocr_infer, inputs=gr.Image(type="pil"), outputs="text", title="Typhoon OCR 1B")
+iface.launch()