Create app.py

app.py

@@ -0,0 +1,30 @@
+import gradio as gr
+import torch
+from transformers import SpeechT5ForTextToSpeech, SpeechT5Processor, SpeechT5HifiGan
+import soundfile as sf
+
+
+model = SpeechT5ForTextToSpeech.from_pretrained("Beehzod/speecht5_finetuned_uz_customData2")
+processor = SpeechT5Processor.from_pretrained("Beehzod/speecht5_finetuned_uz_customData2")
+vocoder = SpeechT5HifiGan.from_pretrained("microsoft/speecht5_hifigan")
+
+speaker_embeddings = torch.zeros((1, 512))
+
+def text_to_speech(text):
+  
+    inputs = processor(text=text, return_tensors="pt")
+    speech = model.generate_speech(inputs["input_ids"], speaker_embeddings, vocoder=vocoder)
+    output_path = "output.wav"
+    sf.write(output_path, speech.numpy(), 16000)
+    return output_path
+
+
+interface = gr.Interface(
+    fn=text_to_speech,
+    inputs="text",
+    outputs="audio",
+    title="Uzbek Text-to-Speech Generator",
+    description="Enter Uzbek text and generate speech using the finetuned SpeechT5 model."
+)
+
+interface.launch()