Create app.py

app.py

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+import torch
+from transformers import AutoTokenizer, VitsModel
+import scipy.io.wavfile
+import gradio as gr
+
+model = VitsModel.from_pretrained("facebook/mms-tts-chv")
+tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-chv")
+
+def tts_chuvash(text):
+    inputs = tokenizer(text, return_tensors="pt")
+    with torch.no_grad():
+        speech = model(**inputs).waveform
+
+    audio_np = speech.squeeze().cpu().numpy()
+    sampling_rate = model.config.sampling_rate
+    return (sampling_rate, audio_np)
+
+demo = gr.Interface(
+    fn=tts_chuvash,
+    inputs=gr.Textbox(label="Текст чăвашла чĕлхи (Chuvash Cyrillic)"),
+    outputs=gr.Audio(label="Аудио"),
+    title="Чăваш TTS (Facebook VITS)",
+    description="Модель TTS на чăваш чĕлхи с помощью MMS-TTS от Facebook (поддерживает только кириллицу)"
+)
+
+demo.launch()