README / app.py
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Create app.py (#1)
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from transformers import pipeline
import gradio as gr
import tempfile
# Load TTS pipeline with a model that works in Spaces
tts = pipeline("text-to-speech", model="facebook/fastspeech2-en-ljspeech")
def greet(name):
greeting = f"Hello {name}!! You're amazing!"
audio_data = tts(greeting)["audio"]
# Save to a temp WAV file
with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as f:
f.write(audio_data)
return f.name
demo = gr.Interface(fn=greet, inputs="text", outputs=gr.Audio(type="filepath"))
demo.launch()