refactor: Streamline model loading by using `load_file` for safetensors and adjusting print statements.

app.py

@@ -48,16 +48,15 @@ AutoModel.register(WhisperEncoderOnlyConfig, WhisperEncoderOnlyForClassification
 # === LOAD MODEL ===
 MODEL_REPO = "tachiwin/language_classification_enconly_model_2"
 
-print("Loading processor and config...")
+print("Loading model...")
 processor = WhisperProcessor.from_pretrained(MODEL_REPO)
 config = WhisperEncoderOnlyConfig.from_pretrained(MODEL_REPO)
-
-print("Downloading model weights...")
-model_path = hf_hub_download(repo_id=MODEL_REPO, filename="model.safetensors")
-
-print("Initializing model...")
 model = WhisperEncoderOnlyForClassification(config)
-state_dict = torch.load(model_path, map_location="cpu")
+
+# Load weights from safetensors
+from huggingface_hub import hf_hub_download
+weights_path = hf_hub_download(repo_id=MODEL_REPO, filename="model.safetensors")
+state_dict = load_file(weights_path)
 model.load_state_dict(state_dict)
 model.eval()