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import gradio as gr
import whisper
model = whisper.load_model("base")
def inference(audio):
result = model.transcribe(audio)
print(result["text"])
return result["text"]
title="Whisper"
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."
css = """
.gradio-container {
font-family: 'IBM Plex Sans', sans-serif;
}
.gr-button {
color: white;
border-color: black;
background: black;
}
input[type='range'] {
accent-color: black;
}
.dark input[type='range'] {
accent-color: #dfdfdf;
}
.container {
max-width: 730px;
margin: auto;
padding-top: 1.5rem;
}
#gallery {
min-height: 22rem;
margin-bottom: 15px;
margin-left: auto;
margin-right: auto;
border-bottom-right-radius: .5rem !important;
border-bottom-left-radius: .5rem !important;
}
#gallery>div>.h-full {
min-height: 20rem;
}
.details:hover {
text-decoration: underline;
}
.gr-button {
white-space: nowrap;
}
.gr-button:focus {
border-color: rgb(147 197 253 / var(--tw-border-opacity));
outline: none;
box-shadow: var(--tw-ring-offset-shadow), var(--tw-ring-shadow), var(--tw-shadow, 0 0 #0000);
--tw-border-opacity: 1;
--tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) var(--tw-ring-offset-color);
--tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(3px var(--tw-ring-offset-width)) var(--tw-ring-color);
--tw-ring-color: rgb(191 219 254 / var(--tw-ring-opacity));
--tw-ring-opacity: .5;
}
.footer {
margin-bottom: 45px;
margin-top: 35px;
text-align: center;
border-bottom: 1px solid #e5e5e5;
}
.footer>p {
font-size: .8rem;
display: inline-block;
padding: 0 10px;
transform: translateY(10px);
background: white;
}
.dark .footer {
border-color: #303030;
}
.dark .footer>p {
background: #0b0f19;
}
.prompt h4{
margin: 1.25em 0 .25em 0;
font-weight: bold;
font-size: 115%;
}
"""
block = gr.Blocks(css=css)
with block:
gr.HTML(
"""
<div style="text-align: center; max-width: 650px; margin: 0 auto;">
<div
style="
display: inline-flex;
gap: 0.8rem;
font-size: 1.75rem;
margin-bottom: 10px;
margin-left: 220px;
justify-content: center;
"
>
<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>
</div>
<div
style="
display: inline-flex;
align-items: center;
gap: 0.8rem;
font-size: 1.75rem;
margin-bottom: 10px;
justify-content: center;
">
<a href="https://github.com/PaddlePaddle/PaddleHub"><h1 style="font-weight: 900; margin-bottom: 7px;">
ERNIE-ViLG Demo
</h1></a>
</div>
<p style="margin-bottom: 10px; font-size: 94%">
ERNIE-ViLG is a state-of-the-art text-to-image model that generates
images from Chinese text.
</p>
<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>
</div>
"""
)
with gr.Group():
with gr.Box():
with gr.Row().style(mobile_collapse=False, equal_height=True):
audio = gr.Audio(
label="Input Audio",
show_label=False,
).style(
border=(True, False, True, True),
rounded=(True, False, False, True),
container=False,
)
btn = gr.Button("Transcribe").style(
margin=False,
rounded=(False, True, True, False),
)
text = gr.Textbox(
).style(height="auto")
btn.click(inference, inputs=[audio], outputs=[text])
gr.HTML('''
<div class="footer">
<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
</p>
</div>
''')
block.launch() |