| import gradio as gr | |
| from transformers import pipeline | |
| def zero_shot_classification(text, labels): | |
| classifier = pipeline("zero-shot-classification", model="models/tasksource/ModernBERT-nli") | |
| result = classifier(text, labels) | |
| return {label: score for label, score in zip(result['labels'], result['scores'])} | |
| default_text = "all cats are blue" | |
| default_labels = ['true', 'false'] | |
| demo = gr.Interface( | |
| fn=zero_shot_classification, | |
| inputs=[ | |
| gr.Textbox(label="Input Text", value=default_text), | |
| gr.Textbox(label="Possible Labels (comma-separated)", value=','.join(default_labels)) | |
| ], | |
| outputs=gr.Label(label="Classification Scores"), | |
| title="Zero-Shot Classification", | |
| description="Classify a text into labels without prior training for the specific labels." | |
| ) | |
| demo.launch() | |