debug

app.py

@@ -417,28 +417,26 @@ def build_demo():
     return demo
 
 
-
-
-
-if __name__ == "__main__":
-    logging.basicConfig(
+logging.basicConfig(
         level=logging.INFO,
         format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
     )
-    logger = logging.getLogger(__name__)
-    logger.info(gr.__version__)
-    from huggingface_hub import snapshot_download
-    huggingface_path = Path(snapshot_download(repo_id="laurenssam/privacy-aware-visual-language-models"))
-    model_name = str(huggingface_path / "tinyllava_demo")
-    tokenizer, model, image_processor, context_len = load_pretrained_model(
-        model_path=str(model_name),
-        model_base="bczhou/TinyLLaVA-3.1B",
-        model_name=get_model_name_from_path(model_name + "_lora_TinyLLaVA-3.1B"),
-        device="cpu",
-        load_4bit=False,
-        load_8bit=False
-    )
-    model = model.cpu().float()
-    demo = build_demo()
-    demo.queue()
+logger = logging.getLogger(__name__)
+logger.info(gr.__version__)
+from huggingface_hub import snapshot_download
+huggingface_path = Path(snapshot_download(repo_id="laurenssam/privacy-aware-visual-language-models"))
+model_name = str(huggingface_path / "tinyllava_demo")
+tokenizer, model, image_processor, context_len = load_pretrained_model(
+    model_path=str(model_name),
+    model_base="bczhou/TinyLLaVA-3.1B",
+    model_name=get_model_name_from_path(model_name + "_lora_TinyLLaVA-3.1B"),
+    device="cpu",
+    load_4bit=False,
+    load_8bit=False
+)
+model = model.cpu().float()
+demo = build_demo()
+demo.queue()
+
+if __name__ == "__main__":
     demo.launch()