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