Upload usage.py

usage.py

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+from transformers import VitsModel, AutoTokenizer
+import torch
+import scipy
+import numpy as np
+
+model = VitsModel.from_pretrained("indonesian-tts")
+tokenizer = AutoTokenizer.from_pretrained("indonesian-tts")
+text ="Saya menelepon dari kantor pajak."
+inputs = tokenizer(text, return_tensors="pt")
+
+with torch.no_grad():
+ output = model(**inputs).waveform
+output_np = output.squeeze().numpy()  # Remove extra dimensions
+output_np = output_np / np.max(np.abs(output_np))  # Normalize to prevent clipping
+            
+scipy.io.wavfile.write(
+                "indonesian.wav",  # Better file naming with padding
+                rate=model.config.sampling_rate,
+                data=output_np
+                )
+