| 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 = [["One day I will see the world", "travel, live, die, future"]] |
|
|
| css = """ |
| footer {display:none !important} |
| .output-markdown{display:none !important} |
| .gr-button-primary { |
| z-index: 14; |
| height: 43px; |
| width: 130px; |
| left: 0px; |
| top: 0px; |
| padding: 0px; |
| cursor: pointer !important; |
| background: none rgb(17, 20, 45) !important; |
| border: none !important; |
| text-align: center !important; |
| font-family: Poppins !important; |
| font-size: 14px !important; |
| font-weight: 500 !important; |
| color: rgb(255, 255, 255) !important; |
| line-height: 1 !important; |
| border-radius: 12px !important; |
| transition: box-shadow 200ms ease 0s, background 200ms ease 0s !important; |
| box-shadow: none !important; |
| } |
| .gr-button-primary:hover{ |
| z-index: 14; |
| height: 43px; |
| width: 130px; |
| left: 0px; |
| top: 0px; |
| padding: 0px; |
| cursor: pointer !important; |
| background: none rgb(37, 56, 133) !important; |
| border: none !important; |
| text-align: center !important; |
| font-family: Poppins !important; |
| font-size: 14px !important; |
| font-weight: 500 !important; |
| color: rgb(255, 255, 255) !important; |
| line-height: 1 !important; |
| border-radius: 12px !important; |
| transition: box-shadow 200ms ease 0s, background 200ms ease 0s !important; |
| box-shadow: rgb(0 0 0 / 23%) 0px 1px 7px 0px !important; |
| } |
| .hover\:bg-orange-50:hover { |
| --tw-bg-opacity: 1 !important; |
| background-color: rgb(229,225,255) !important; |
| } |
| |
| to-orange-200 { |
| --tw-gradient-to: rgb(37 56 133 / 37%) !important; |
| } |
| |
| from-orange-400 { |
| --tw-gradient-from: rgb(17, 20, 45) !important; |
| --tw-gradient-stops: var(--tw-gradient-from), var(--tw-gradient-to) !important; |
| } |
| |
| .group:hover .group-hover\:border-orange-400 { |
| --tw-border-opacity: 1; |
| border-color: rgb(37 56 133 / var(--tw-border-opacity)); |
| } |
| |
| .group:hover .group-hover\:from-orange-500 { |
| --tw-gradient-from: rgb(17, 20, 45) !important; |
| --tw-gradient-to: rgb(37 56 133 / 0) !important; |
| --tw-gradient-stops: var(--tw-gradient-from), var(--tw-gradient-to) !important; |
| } |
| |
| """ |
|
|
| 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) |
| demo.launch() |
