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import gradio as gr | |
title = "Mushroom Gallery" | |
tts_examples = [ | |
"I love learning machine learning", | |
"How do you do?", | |
] | |
tts_demo = gr.Interface.load( | |
"huggingface/facebook/fastspeech2-en-ljspeech", | |
title=None, | |
examples=tts_examples, | |
description="Give me something to say!", | |
) | |
vision_demo = gr.Interface.load( | |
"models/google/vit-base-patch16-224", | |
title=None, | |
description="Image Classification", | |
) | |
stt_demo = gr.Interface.load( | |
"huggingface/facebook/wav2vec2-base-960h", | |
title=None, | |
inputs="mic", | |
description="Let me try to guess what you're saying!", | |
) | |
demo = gr.TabbedInterface([vision_demo, tts_demo, stt_demo], ["Image Classification", "Text-to-speech", "Speech-to-text"]) | |
if __name__ == "__main__": | |
demo.launch() | |