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import gradio as gr | |
# Text to Speech Interface | |
tts_title = "Text to Speech Translation" | |
tts_examples = [ | |
"I love learning machine learning", | |
"How do you do?", | |
] | |
tts_demo = gr.Interface.load( | |
"huggingface/facebook/fastspeech2-en-ljspeech", | |
title=tts_title, | |
examples=tts_examples, | |
description="Give me something to say!", | |
) | |
# Sentiment Analysis Interface | |
sentiment_title = "Sentiment Analysis" | |
sentiment_examples = [ | |
"I love learning machine learning", | |
"How do you do?", | |
] | |
sentiment_demo = gr.Interface.load( | |
"huggingface/nlp-sentiment-analysis", | |
title=sentiment_title, | |
examples=sentiment_examples, | |
description="Analyze the sentiment of the text!", | |
) | |
# Tabbed Interface | |
demo = gr.TabbedInterface([tts_demo, sentiment_demo], ["Text to Speech", "Sentiment Analysis"]) | |
if __name__ == "__main__": | |
demo.launch() |