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import gradio as gr
from transformers import pipeline
model_id = "Subhajit01/distilbert-base-uncased-finetuned-emotion"
classifier = pipeline("text-classification", model=model_id)
labels = ['sadness', 'joy', 'love', 'anger', 'fear', 'surprise']
def predict(text):
max_prob_id = 0
max_prob = 0
preds = classifier(text, return_all_scores=True)
for i in range(len(preds[0])):
if (preds[0][i]["score"] > max_prob):
max_prob = preds[0][i]["score"]
max_prob_id = i
return labels[max_prob_id]
iface = gr.Interface(fn=predict,
inputs="text",
outputs="text",
title="Sentiment Analyzer",
description="Enter text to analyze its sentiment.")
iface.launch(share= True) |