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import gradio as gr |
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from transformers import pipeline |
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classifier = pipeline("zero-shot-classification", model="facebook/bart-large-mnli") |
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def zeroShotClassification(text_input, candidate_labels): |
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labels = [label.strip(' ') for label in candidate_labels.split(',')] |
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output = {} |
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prediction = classifier(text_input, labels) |
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for i in range(len(prediction['labels'])): |
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output[prediction['labels'][i]] = prediction['scores'][i] |
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return output |
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examples = [["One day I will see the world", "travel, live, die, future"]] |
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css = """ |
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footer {display:none !important} |
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.output-markdown{display:none !important} |
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.gr-button-primary { |
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z-index: 14; |
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height: 43px; |
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width: 130px; |
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left: 0px; |
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top: 0px; |
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padding: 0px; |
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cursor: pointer !important; |
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background: none rgb(17, 20, 45) !important; |
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border: none !important; |
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text-align: center !important; |
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font-family: Poppins !important; |
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font-size: 14px !important; |
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font-weight: 500 !important; |
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color: rgb(255, 255, 255) !important; |
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line-height: 1 !important; |
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border-radius: 12px !important; |
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transition: box-shadow 200ms ease 0s, background 200ms ease 0s !important; |
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box-shadow: none !important; |
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} |
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.gr-button-primary:hover{ |
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z-index: 14; |
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height: 43px; |
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width: 130px; |
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left: 0px; |
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top: 0px; |
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padding: 0px; |
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cursor: pointer !important; |
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background: none rgb(37, 56, 133) !important; |
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border: none !important; |
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text-align: center !important; |
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font-family: Poppins !important; |
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font-size: 14px !important; |
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font-weight: 500 !important; |
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color: rgb(255, 255, 255) !important; |
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line-height: 1 !important; |
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border-radius: 12px !important; |
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transition: box-shadow 200ms ease 0s, background 200ms ease 0s !important; |
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box-shadow: rgb(0 0 0 / 23%) 0px 1px 7px 0px !important; |
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} |
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.hover\:bg-orange-50:hover { |
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--tw-bg-opacity: 1 !important; |
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background-color: rgb(229,225,255) !important; |
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} |
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to-orange-200 { |
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--tw-gradient-to: rgb(37 56 133 / 37%) !important; |
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} |
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from-orange-400 { |
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--tw-gradient-from: rgb(17, 20, 45) !important; |
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--tw-gradient-stops: var(--tw-gradient-from), var(--tw-gradient-to) !important; |
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} |
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.group:hover .group-hover\:border-orange-400 { |
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--tw-border-opacity: 1; |
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border-color: rgb(37 56 133 / var(--tw-border-opacity)); |
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} |
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.group:hover .group-hover\:from-orange-500 { |
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--tw-gradient-from: rgb(17, 20, 45) !important; |
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--tw-gradient-to: rgb(37 56 133 / 0) !important; |
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--tw-gradient-stops: var(--tw-gradient-from), var(--tw-gradient-to) !important; |
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} |
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""" |
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demo = gr.Interface(fn=zeroShotClassification, inputs=[gr.Textbox(label="Input"), gr.Textbox(label="Candidate Labels")], outputs=gr.Label(label="Classification"), title="Zero Shot Text Classification | Datascience Dojo", examples=examples, css=css) |
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demo.launch() |