app.py

from transformers import pipeline
import gradio as gr

classifier = pipeline("zero-shot-classification", model="DeepPavlov/xlm-roberta-large-en-ru-mnli")

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=5, label="Text to classify"),
        gr.inputs.Textbox(lines=1, label="Candidate labels separated with commas"),
        gr.inputs.Textbox(lines=1, label="Template", default="This sentence is about {}.", placeholder="This sentence is about {}.")
    ],
    outputs=[
        gr.outputs.Textbox(label="Label")
    ],
    enable_queue=True,
    allow_screenshot=False,
    allow_flagging=False
).launch(debug=True)