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from transformers import pipeline
import gradio as gr
classifier = pipeline("zero-shot-classification", model="oigele/Fb_improved_zeroshot")
def wrap_classifier(text, labels, template):
labels = labels.split(",")
outputs = classifier(text, labels, hypothesis_template=template)
return outputs["labels"][0]
gr.Interface(
fn=wrap_classifier,
title="Zero-shot Classification",
inputs=[
gr.inputs.Textbox(
lines=3,
label="Text to classify",
default="Furry fandom"
),
gr.inputs.Textbox(
lines=1,
label="Candidate labels separated with commas (no spaces)",
default="good,bad",
placeholder="good,bad",
),
gr.inputs.Textbox(lines=1, label="Template", default="Asexuality is {}.", placeholder="Asexuality is {}.")
],
outputs=[
gr.outputs.Textbox(label="Predicted label")
],
enable_queue=True,
allow_screenshot=False,
allow_flagging=False,
# examples=[
# ["Indian state rolls out wireless broadband Government in South Indian state of Kerala sets up wireless kiosks as part of initiative to bridge digital divide."]
# ]
).launch(debug=True) |