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import gradio as gr
from text2tags import TaggerLlama
model = TaggerLlama()
def predict(caption, max_tokens=128, temperature=0.8, top_k=40, top_p=0.95, repeat_penalty=1.1):
tags = model.predict_tags(caption, max_tokens=max_tokens, temperature=temperature,
top_k=top_k, top_p=top_p, repeat_penalty=repeat_penalty)
return ', '.join(tags)
description = """
### Enter a caption to extract danbooru tags from it.
[  ](https://github.com/DatboiiPuntai/text2tags-lib)
"""
demo = gr.Interface(
fn=predict,
inputs=[
gr.Textbox(label="Caption"),
gr.Slider(0, 256, step=16, value=128, label='max_tokens'),
gr.Slider(0, 2, step=0.1, value=0.8, label='temperature'),
gr.Slider(0, 100, step=5, value=40, label='top_k'),
gr.Slider(0, 2, step=0.05, value=0.95, label='top_p'),
gr.Slider(0, 5, step=0.1, value=1.1, label='repeat_penalty'),
],
outputs="text",
title="Text2Tags",
description=description,
examples=[
["Minato Aqua from hololive with pink and blue twintails in a blue maid outfit"],
],
allow_flagging="never"
)
demo.launch()
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