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import gradio as gr | |
from transformers import pipeline | |
# Load model locally (no API call) | |
emotion_classifier = pipeline("text-classification", model="j-hartmann/emotion-english-distilroberta-base", return_all_scores=True) | |
def detect_emotion(text): | |
results = emotion_classifier(text)[0] | |
return {res["label"]: res["score"] for res in results} | |
iface = gr.Interface(fn=detect_emotion, | |
inputs="text", | |
outputs="label", | |
title="Emotion Detection", | |
description="Enter text to detect emotion using DistilRoBERTa") | |
iface.launch() | |