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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,
)
EMOTIONS = ["sadness", "joy", "love", "anger", "fear", "surprise"]
def predict_emotion(text):
results = classifier(text)[0]
return {result["label"]: result["score"] for result in results if result["label"] in EMOTIONS}
iface = gr.Interface(
fn=predict_emotion,
inputs=gr.Textbox(lines=3, placeholder="Enter text here..."),
outputs=gr.Label(num_top_classes=6),
title="Creative Machines: Sentiment Analysis",
description="Enter some text and see the predicted emotions.",
)
if __name__ == "__main__":
iface.launch()
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