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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!", | |
) | |
anime_demo = gr.Interface.load( | |
"spaces/akhaliq/AnimeGANv2", | |
title=None, | |
description="Anime GAN", | |
) | |
vision_demo = gr.Interface.load( | |
"models/google/vit-base-patch16-224", | |
title=None, | |
description="Vision Transformer", | |
) | |
chatgpt3_demo = gr.Interface.load( | |
"spaces/mushroomsolutions/chatgpt-3", | |
title=None, | |
description="Chat GPT3", | |
) | |
sentiment_demo = gr.Interface.load( | |
"models/LiYuan/amazon-review-sentiment-analysis", | |
title=None, | |
description="Amazon Reviews", | |
) | |
stt_demo = gr.Interface.load( | |
"huggingface/facebook/wav2vec2-base-960h", | |
title=None, | |
inputs="mic", | |
description="Let me try to guess what you're saying!", | |
) | |
Medical_Image_Classification_demo = gr.Interface.load( | |
"spaces/mushroomsolutions/Medical-Image-Classification", | |
title=None, | |
description="Medical Image Classification", | |
) | |
with gr.Blocks() as demo: | |
gr.Markdown("<h2>Welcome to Mushrooom Solutions - AI ML Showcase</h2>") | |
gr.TabbedInterface([vision_demo, sentiment_demo, anime_demo, Medical_Image_Classification_demo, chatgpt3_demo, tts_demo, stt_demo], | |
["Image Classification", "Sentiment Analysis", "Anime", "Medical Image Classification", "Chat GPT3", "Text-to-speech", "Speech-to-text"]) | |
if __name__ == "__main__": | |
demo.launch() |