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import gradio as gr | |
from transformers import pipeline | |
classifier = pipeline("zero-shot-classification") | |
labels = ["No Connectivity", "Billing", "Setup", "Slow Connection"] | |
def predict(text): | |
preds = classifier(text, candidate_labels=labels) | |
return {label: float(pred) for label, pred in zip(preds["labels"], preds["scores"])} | |
input = gr.inputs.Textbox(label="Customer Sentence") | |
output = gr.outputs.Label(num_top_classes=4, label="Zero-Shot-Classification") | |
title = "Case Classification" | |
description = "Zero-Shot-Classification test" | |
gr.Interface(predict, input, output, live=False, live_update=False, title=title, analytics_enabled=False, | |
description=description, capture_session=True).launch() |