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from fastai.text.all import*
import gradio as gr
learn = load_learner('nlp_model.pkl')
labels = learn.dls.vocab
emotion_labels = labels[1]
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 {emotion_labels[i]: float(probs[i]) for i in range(len(emotion_labels))}
interface = gr.Interface(
fn=classify_text,
inputs=gr.components.Textbox(
placeholder="Enter Text here",
label='Input text',
lines=5
),
outputs=gr.components.Label(
num_top_classes=4,
label='Emotion in the Text'
),
title="Emotion Classifier",
theme='soft'
)
interface.launch()
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