Refactor: Simplify model loading by directly using `from_pretrained` for `WhisperEncoderOnlyForClassification` and removing explicit config and weight loading.

app.py

@@ -51,13 +51,13 @@ MODEL_REPO = "tachiwin/language_classification_enconly_model_2"
 
 print("Loading model on CPU...")
 processor = WhisperProcessor.from_pretrained(MODEL_REPO)
-config = WhisperEncoderOnlyConfig.from_pretrained(MODEL_REPO)
-model = WhisperEncoderOnlyForClassification(config)
+#config = WhisperEncoderOnlyConfig.from_pretrained(MODEL_REPO)
+model = WhisperEncoderOnlyForClassification.from_pretrained(MODEL_REPO)
 
 # Load weights from safetensors
-weights_path = hf_hub_download(repo_id=MODEL_REPO, filename="model.safetensors")
-state_dict = load_file(weights_path)
-model.load_state_dict(state_dict)
+#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()
 
 print("Model loaded successfully!")