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import gradio as gr
import paddlehub as hub
ernie_zeus = hub.Module(name='ernie_zeus')
def inference(task: str,
text: str,
min_dec_len: int = 2,
seq_len: int = 512,
topp: float = 0.9,
penalty_score: float = 1.0):
func = getattr(ernie_zeus, task)
try:
result = func(text, min_dec_len, seq_len, topp, penalty_score)
return result
except Exception as error:
return str(error)
title = "ERNIE-Zeus"
description = "ERNIE-Zeus model, which supports Chinese text generates task."
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;
}
.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)
examples = [
[
'text_summarization',
'外媒7月18日报道,阿联酋政府当日证实该国将建设首个核电站,以应对不断上涨的用电需求。分析称阿联酋作为世界第三大石油出口国,更愿意将该能源用于出口,而非发电。首座核反应堆预计在2017年运行。cntv李婉然编译报道',
4, 512, 0.3, 1.0
],
[
'copywriting_generation',
'芍药香氛的沐浴乳',
8, 512, 0.9, 1.2
],
[
'novel_continuation',
'昆仑山可以说是天下龙脉的根源,所有的山脉都可以看作是昆仑的分支。这些分出来的枝枝杈杈,都可以看作是一条条独立的龙脉。',
2, 512, 0.9, 1.2
],
[
'answer_generation',
'做生意的基本原则是什么?',
2, 512, 0.5, 1.2
],
[
'couplet_continuation',
'天增岁月人增寿',
2, 512, 1.0, 1.0
],
[
'composition_generation',
'拔河比赛',
128, 512, 0.9, 1.2
],
[
'text_cloze',
'她有着一双[MASK]的眼眸。',
1, 512, 0.3, 1.2
],
]
with block:
gr.HTML(
"""
<div style="text-align: center; max-width: 650px; margin: 0 auto;">
<div
style="
display: inline-flex;
align-items: center;
gap: 0.8rem;
font-size: 1.75rem;
margin-bottom: 10px;
justify-content: center;
"
>
<img src="https://user-images.githubusercontent.com/22424850/187387422-f6c9ccab-7fda-416e-a24d-7d6084c46f67.jpg" alt="Paddlehub" width="40%">
</div>
<div
style="
display: inline-flex;
align-items: center;
gap: 0.8rem;
font-size: 1.75rem;
margin-bottom: 10px;
justify-content: center;
">
<h1 style="font-weight: 900; margin-bottom: 7px;">
ERNIE-Zeus Demo
</h1>
</div>
<p style="margin-bottom: 10px; font-size: 94%">
ERNIE-Zeus is a state-of-the-art Chinese text generates model.
</p>
</div>
"""
)
with gr.Blocks():
text = gr.Textbox(
label="input_text",
placeholder="Please enter Chinese text.",
)
task = gr.Dropdown(label="task",
choices=[
'text_summarization',
'copywriting_generation',
'novel_continuation',
'answer_generation',
'couplet_continuation',
'composition_generation',
'text_cloze'
],
value='text_summarization')
min_dec_len = gr.Slider(
minimum=1, maximum=511, value=1, label="min_dec_len", step=1, interactive=True)
seq_len = gr.Slider(minimum=2, maximum=512, value=128,
label="seq_len", step=1, interactive=True)
topp = gr.Slider(minimum=0.0, maximum=1.0, value=1.0,
label="topp", step=0.01, interactive=True)
penalty_score = gr.Slider(
minimum=1.0, maximum=2.0, value=1.0, label="penalty_score", step=0.01, interactive=True)
text_gen = gr.Textbox(label="generated_text")
btn = gr.Button(value="Generate text")
ex = gr.Examples(examples=examples, fn=inference, inputs=[
task, text, min_dec_len, seq_len, topp, penalty_score], outputs=text_gen, cache_examples=False)
text.submit(inference, inputs=[
task, text, min_dec_len, seq_len, topp, penalty_score], outputs=text_gen)
btn.click(inference, inputs=[
task, text, min_dec_len, seq_len, topp, penalty_score], outputs=text_gen)
gr.Markdown(
'''
## More
* There are more interesting models in [PaddleHub](https://github.com/PaddlePaddle/PaddleHub), you can star [PaddleHub](https://github.com/PaddlePaddle/PaddleHub) to follow.
* Besides, you can use free GPU resourses in [AIStudio](https://aistudio.baidu.com/aistudio/projectdetail/4462918) to enjoy more cases, have fun.
[![](https://user-images.githubusercontent.com/22424850/187849103-074cb6d2-a9b4-49a1-b1f0-fc130049769f.png)](https://github.com/PaddlePaddle/PaddleHub/stargazers)
'''
)
gr.HTML(
"""
<div class="footer">
<p>Model by <a href="https://github.com/PaddlePaddle/PaddleHub" style="text-decoration: underline;" target="_blank">PaddleHub</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.queue(max_size=100000, concurrency_count=100000).launch()
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