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import gradio as gr | |
from transformers import pipeline | |
# Load pre-trained model from Hugging Face | |
classifier = pipeline('sentiment-analysis') | |
def classify_text(text): | |
result = classifier(text)[0] | |
label = result['label'] | |
score = result['score'] | |
return f"{label} (confidence: {score:.2f})" | |
# Create the Gradio interface | |
iface = gr.Interface(fn=classify_text, inputs=["text"], outputs=["prediction"]) | |
# Launch the Gradio app | |
iface.launch() | |