| 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() | |