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import os |
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os.system("pip uninstall -y gradio") |
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os.system("pip install gradio==3.40.1") |
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import argparse |
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import gradio as gr |
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from demo.generation_frontend import build_generation |
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from demo.chat_frontend import build_chat |
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parser = argparse.ArgumentParser() |
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parser.add_argument("--title", type=str, default='Emu') |
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parser.add_argument("--host", type=str, default="0.0.0.0") |
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parser.add_argument("--port", type=int, default=9002) |
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parser.add_argument("--share", action="store_true") |
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parser.add_argument("--controller-url", type=str, default="http://218.91.113.230:9003") |
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parser.add_argument("--concurrency-count", type=int, default=2) |
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parser.add_argument("--disable-chat", action="store_true") |
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parser.add_argument("--disable-generate", action="store_true") |
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args = parser.parse_args() |
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if __name__ == "__main__": |
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title = "Emu2: Generative Multimodal Models are In-Context Learners<br> \ |
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<div align='center'> \ |
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<h2>|<a href='https://arxiv.org/abs/2307.05222' target='_blank' rel='noopener'>paper</a>| \ |
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|<a href='https://github.com/baaivision/Emu' target='_blank' rel='noopener'>code</a>|</h2> \ |
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</div> \ |
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<div align='center'> \ |
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<h2>|<a href='https://jwolpxeehx.feishu.cn/docx/KskPdU99FomufKx4G9hcQMeQnHv' target='_blank' rel='noopener'>使用说明</a>| \ |
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|<a href='https://jwolpxeehx.feishu.cn/docx/RYHNd1tvEo8k8Mx9HeMcvvxWnvZ' target='_blank' rel='noopener'>User Guide</a>|</h2> \ |
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<div align='left'> \ |
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" |
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interface_list, tab_names = [], [] |
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if not args.disable_generate: |
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demo_generation = build_generation(args) |
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interface_list.append(demo_generation) |
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tab_names.append("Multi-modal Generation") |
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if not args.disable_chat: |
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demo_chat = build_chat(args) |
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interface_list.append(demo_chat) |
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tab_names.append("Multi-modal Chat") |
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demo_all = gr.TabbedInterface( |
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interface_list=interface_list, |
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tab_names=tab_names, |
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title=title, |
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theme=gr.themes.Default(primary_hue="blue", secondary_hue="blue"), |
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) |
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demo_all.queue( |
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concurrency_count=args.concurrency_count, |
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status_update_rate=3, |
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api_open=False, |
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).launch( |
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enable_queue=True, |
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share=args.share, |
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) |
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