Tramsformer / app.py
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import streamlit as st
import numpy
from transformers import pipeline
from IPython.display import Audio
classifier = pipeline("text-to-speech", model="GuGai/text_to_speech_G")
def main():
st.title("Text to Speech")
with st.form("text_field"):
text = st.text_area('enter some text:')
# clicked==True only when the button is clicked
clicked = st.form_submit_button("Submit text")
if clicked:
results = classifier(text)
st.json(results)
Audio(results['audio'], rate=results['sampling_rate'])
if __name__ == "__main__":
main()