Create handler.py

wav2vec2-pretrained-demo3/handler.py

@@ -0,0 +1,17 @@
+from transformers import AutoModelForAudioClassification
+
+class CustomAudioClassifier(AutoModelForAudioClassification):
+    def __init__(self, config):
+        super().__init__(config)
+        # Add custom initialization logic if needed
+
+    def forward(self, input_values, **kwargs):
+        # Customize the forward pass of the model
+        outputs = super().forward(input_values, **kwargs)
+        # Add custom logic here, e.g., post-processing of outputs
+        return outputs
+
+# Example usage:
+# Initialize your custom audio classifier
+custom_classifier = CustomAudioClassifier.from_pretrained('./model.safetensors')
+# Use the custom classifier for inference or fine-tuning