Add application file

app.py

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+import gradio as gr
+import torch
+import numpy as np
+from transformers import VitsModel, AutoTokenizer
+
+# Configuración del modelo
+model_id = "facebook/mms-tts-yua"
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+print(f"Cargando modelo en: {device}")
+model = VitsModel.from_pretrained(model_id).to(device)
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+
+def generate_tts(text):
+    if not text.strip():
+        return None
+    
+    inputs = tokenizer(text, return_tensors="pt").to(device)
+    
+    with torch.no_grad():
+        output = model(**inputs)
+    
+    waveform = output.waveform[0].cpu().numpy()
+    sample_rate = model.config.sampling_rate
+    
+    return (sample_rate, waveform)
+
+# Interfaz de Gradio
+demo = gr.Interface(
+    fn=generate_tts,
+    inputs=gr.Textbox(label="Escribe en Maya Yucateco", placeholder="Bix yanilech..."),
+    outputs=gr.Audio(label="Audio Generado"),
+    title="Maya Yucateco TTS (Facebook MMS)",
+    description="Servidor de síntesis de voz para el idioma Maya Yucateco."
+)
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+transformers
+accelerate
+torch
+scipy
+numpy