Create app.py

import gradio as gr
from transformers import AutoModelForSpeechSeq2Seq, AutoTokenizer, pipeline

tokenizer = AutoTokenizer.from_pretrained("MarcNg/fastspeech2-vi-infore")
model = AutoModelForSpeechSeq2Seq.from_pretrained("MarcNg/fastspeech2-vi-infore")

tts_pipeline = pipeline("text-to-speech", model=model, tokenizer=tokenizer)

def text_to_speech(text):
output = tts_pipeline(text)
return output["audio"].numpy()

iface = gr.Interface(
fn=text_to_speech,
inputs="text",
outputs="audio",
title="Vietnamese Text-to-Speech",
description="Enter Vietnamese text to convert to speech using FastSpeech 2 model."
)

iface.launch()

app.py

@@ -0,0 +1,3 @@
+transformers
+gradio
+soundfile