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import gradio as gr
from transformers import pipeline
classifier = pipeline("zero-shot-classification", model="facebook/bart-large-mnli")
def zeroShotClassification(text_input, candidate_labels):
labels = [label.strip(' ') for label in candidate_labels.split(',')]
output = {}
prediction = classifier(text_input, labels)
for i in range(len(prediction['labels'])):
output[prediction['labels'][i]] = prediction['scores'][i]
return output
examples = [["I made education free for students", "education, cost, needs, future"]]
demo = gr.Interface(fn=zeroShotClassification, inputs=[gr.Textbox(label="Input"), gr.Textbox(label="Candidate Labels")], outputs=gr.Label(label="Classification"), title="Umer Text Classification", examples=examples,)
demo.launch(True) |