Update app.py

app.py

@@ -198,7 +198,7 @@ class DiffusionBuilder:
         optimizer = torch.optim.AdamW(self.pipeline.unet.parameters(), lr=1e-5)
         self.pipeline.unet.train()
         for epoch in range(epochs):
-            with—for st.spinner(f"Training diffusion epoch {epoch + 1}/{epochs}... ⚙️"):
+            with st.spinner(f"Training diffusion epoch {epoch + 1}/{epochs}... ⚙️"):
                 total_loss = 0
                 for batch in dataloader:
                     optimizer.zero_grad()
@@ -371,7 +371,8 @@ async def process_ocr(image, output_file):
     start_time = time.time()
     status = st.empty()
     status.text("Processing GOT-OCR2_0... (0s)")
-    tokenizer, model = load_ocr_got()
+    tokenizer = AutoTokenizer.from_pretrained("ucaslcl/GOT-OCR2_0", trust_remote_code=True)
+    model = AutoModel.from_pretrained("ucaslcl/GOT-OCR2_0", trust_remote_code=True, torch_dtype=torch.float32).to("cpu").eval()
     result = model.chat(tokenizer, image, ocr_type='ocr')
     elapsed = int(time.time() - start_time)
     status.text(f"GOT-OCR2_0 completed in {elapsed}s!")