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from fastai.text.all import*
import gradio as gr
learn = load_learner('nlp_model.pkl')
labels = learn.dls.vocab
examples = ["I can't believe you lied to me again! This is unacceptable!",
"Got a surprise gift today, feeling overjoyed!"]
def classify_text(text):
pred,pred_idx,probs = learn.predict(text)
return {labels[i]: float(probs[i]) for i in range(len(labels))}
interface = gr.Interface(fn=classify_text,
inputs = gr.inputs.Texbox(placeholder="Enter Text here", label='Input text',lines=5)),
outputs=gr.outputs.Label(num_top_classes=4, label='Emotion inthe Text'),
verbose=True,
title="Emotion Classifier",
theme='soft')
interface.launch()
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