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import gradio as gr |
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from transformers import pipeline |
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classifier = pipeline("text-classification",model='bhadresh-savani/distilbert-base-uncased-emotion', return_all_scores=True) |
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def detect_emotions(emotion_input): |
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prediction = classifier(emotion_input,) |
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output = {} |
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for emotion in prediction[0]: |
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output[emotion["label"]] = emotion["score"] |
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return output |
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examples = [["I am excited to announce that I have been promoted"], ["Sorry for the late reply"]] |
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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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""" |
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demo = gr.Interface(fn=detect_emotions, inputs=gr.Textbox(placeholder="Enter text here", label="Input"), outputs=gr.Label(label="Emotion"), title="Emotion Detector | Datascience Dojo", examples=examples, css=css) |
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demo.launch() |