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| import gradio as gr | |
| from transformers import pipeline | |
| classifier = pipeline("zero-shot-classification", model="Jiva/xlm-roberta-large-it-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 = [["One day I will see the world", "travel, live, die, future"]] | |
| demo = gr.Interface(fn=zeroShotClassification, inputs=["text", "text"], outputs="label", title="Text Classification", examples=examples) | |
| demo.launch() |