Create v2 App.py

v2 App.py

@@ -0,0 +1,27 @@
+import torch
+from transformers import GPT2Tokenizer, GPT2LMHeadModel
+
+class AdvancedVoiceCloningModel(GPT2LMHeadModel):
+    def __init__(self, config):
+        super().__init__(config)
+        # Add additional parameters for controlling wetness or other advanced options
+        
+    def forward(self, input_ids, **kwargs):
+        # Implement forward pass with additional parameters
+        outputs = super().forward(input_ids, **kwargs)
+        # Apply adjustments based on advanced options
+        
+        return outputs
+
+# Example usage
+tokenizer = GPT2Tokenizer.from_pretrained('gpt2')
+model = AdvancedVoiceCloningModel.from_pretrained('gpt2')
+
+input_text = "Hello, how are you?"
+input_ids = tokenizer.encode(input_text, return_tensors='pt')
+
+# Generate synthesized voice with advanced options
+output = model.generate(input_ids, max_length=100)
+decoded_output = tokenizer.decode(output[0], skip_special_tokens=True)
+
+print(decoded_output)