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import gradio as gr | |
from transformers import pipeline | |
from huggingface_hub import login | |
login(token="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") | |
def generate_text( | |
model, | |
text, | |
min_length, | |
max_length, | |
do_not_truncate, | |
): | |
pipe = pipeline( | |
'text-generation', | |
model='MesonWarrior/gpt2-vk-bugro', | |
tokenizer='MesonWarrior/gpt2-vk-bugro', | |
min_length=min_length, | |
max_length=max_length, | |
# do_not_truncate=do_not_truncate, | |
use_auth_token=True | |
) | |
print('generating...') | |
output = pipe(text) | |
print(output) | |
return output[0]['generated_text'] | |
def interface(): | |
with gr.Row(): | |
with gr.Column(): | |
with gr.Row(): | |
model = gr.Dropdown( | |
["Бугро", "Юморески", "Калик"], label="Model", value="Бугро", | |
) | |
text = gr.Textbox(lines=7, label="Input text") | |
output = gr.Textbox(lines=12, label="Output text") | |
with gr.Row(): | |
with gr.Column(): | |
min_length = gr.Slider( | |
minimum=0, maximum=128, value=32, step=1, | |
label="Min Length", | |
) | |
max_length = gr.Slider( | |
minimum=0, maximum=512, value=96, step=1, | |
label="Max Length", | |
) | |
# do_not_truncate = gr.Checkbox( | |
# True, | |
# label="Do not truncate" | |
# ) | |
with gr.Column(): | |
with gr.Row(): | |
generate_btn = gr.Button( | |
"Generate", variant="primary", label="Generate", | |
) | |
generate_btn.click( | |
fn=generate_text, | |
inputs=[ | |
model, | |
text, | |
min_length, | |
max_length, | |
do_not_truncate | |
], | |
outputs=output, | |
) | |
with gr.Blocks( | |
title="GPT2 VK") as demo: | |
gr.Markdown(""" | |
## GPT2 VK | |
Файнтюны модели [ai-forever/rugpt3medium_based_on_gpt2](https://huggingface.co/ai-forever/rugpt3medium_based_on_gpt2) по вашим любимым пабликам ВКонтакте. | |
""") | |
interface() | |
demo.queue().launch() |