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app.py
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import gradio as gr
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import whisper
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model = whisper.load_model("base")
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def inference(audio):
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result = model.transcribe(audio)
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print(result["text"])
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return result["text"]
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title="Whisper"
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description="Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multi-task model that can perform multilingual speech recognition as well as speech translation and language identification."
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css = """
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.gradio-container {
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font-family: 'IBM Plex Sans', sans-serif;
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}
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.gr-button {
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color: white;
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border-color: black;
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background: black;
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}
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input[type='range'] {
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accent-color: black;
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}
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.dark input[type='range'] {
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accent-color: #dfdfdf;
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}
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.container {
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max-width: 730px;
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margin: auto;
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padding-top: 1.5rem;
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}
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#gallery {
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min-height: 22rem;
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margin-bottom: 15px;
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margin-left: auto;
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margin-right: auto;
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border-bottom-right-radius: .5rem !important;
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border-bottom-left-radius: .5rem !important;
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}
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#gallery>div>.h-full {
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min-height: 20rem;
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}
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.details:hover {
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text-decoration: underline;
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}
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.gr-button {
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white-space: nowrap;
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}
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.gr-button:focus {
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border-color: rgb(147 197 253 / var(--tw-border-opacity));
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outline: none;
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box-shadow: var(--tw-ring-offset-shadow), var(--tw-ring-shadow), var(--tw-shadow, 0 0 #0000);
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--tw-border-opacity: 1;
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--tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) var(--tw-ring-offset-color);
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--tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(3px var(--tw-ring-offset-width)) var(--tw-ring-color);
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--tw-ring-color: rgb(191 219 254 / var(--tw-ring-opacity));
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--tw-ring-opacity: .5;
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}
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.footer {
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margin-bottom: 45px;
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margin-top: 35px;
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text-align: center;
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border-bottom: 1px solid #e5e5e5;
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}
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.footer>p {
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font-size: .8rem;
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display: inline-block;
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padding: 0 10px;
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transform: translateY(10px);
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background: white;
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}
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.dark .footer {
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border-color: #303030;
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}
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.dark .footer>p {
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background: #0b0f19;
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}
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.prompt h4{
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margin: 1.25em 0 .25em 0;
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font-weight: bold;
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font-size: 115%;
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}
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"""
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block = gr.Blocks(css=css)
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with block:
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gr.HTML(
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"""
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<div style="text-align: center; max-width: 650px; margin: 0 auto;">
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<div
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style="
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display: inline-flex;
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gap: 0.8rem;
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font-size: 1.75rem;
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margin-bottom: 10px;
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margin-left: 220px;
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justify-content: center;
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"
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>
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<a href="https://github.com/PaddlePaddle/PaddleHub"><img src="https://user-images.githubusercontent.com/22424850/187387422-f6c9ccab-7fda-416e-a24d-7d6084c46f67.jpg" alt="Paddlehub" width="40%"></a>
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</div>
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<div
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style="
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display: inline-flex;
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align-items: center;
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gap: 0.8rem;
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font-size: 1.75rem;
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margin-bottom: 10px;
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justify-content: center;
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">
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<a href="https://github.com/PaddlePaddle/PaddleHub"><h1 style="font-weight: 900; margin-bottom: 7px;">
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ERNIE-ViLG Demo
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</h1></a>
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</div>
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<p style="margin-bottom: 10px; font-size: 94%">
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ERNIE-ViLG is a state-of-the-art text-to-image model that generates
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images from Chinese text.
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</p>
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<a href="https://github.com/PaddlePaddle/PaddleHub"><img src="https://user-images.githubusercontent.com/22424850/188184795-98605a22-9af2-4106-827b-e58548f8892f.png" alt="star Paddlehub" width="100%"></a>
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</div>
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"""
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)
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with gr.Group():
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with gr.Box():
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with gr.Row().style(mobile_collapse=False, equal_height=True):
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audio = gr.Audio(
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label="Input Audio",
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show_label=False,
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).style(
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border=(True, False, True, True),
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rounded=(True, False, False, True),
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container=False,
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)
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btn = gr.Button("Transcribe").style(
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margin=False,
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rounded=(False, True, True, False),
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)
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text = gr.Textbox(
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).style(height="auto")
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btn.click(inference, inputs=[audio], outputs=[text])
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gr.HTML('''
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<div class="footer">
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<p>Model by <a href="https://github.com/openai/whisper" style="text-decoration: underline;" target="_blank">OpenAI</a> and <a href="https://wenxin.baidu.com" style="text-decoration: underline;" target="_blank">文心大模型</a> - Gradio Demo by 🤗 Hugging Face
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</p>
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</div>
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''')
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block.launch()
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