|
import torch |
|
import gradio as gr |
|
from transformers import pipeline |
|
|
|
|
|
sentiment_analysis = pipeline("sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english") |
|
|
|
|
|
def analyze_sentiment(input_text): |
|
|
|
result = sentiment_analysis(input_text) |
|
|
|
label = result[0]['label'] |
|
confidence = round(result[0]['score'] * 100, 2) |
|
return f"Sentiment: {label} (Confidence: {confidence}%)" |
|
|
|
|
|
gr.close_all() |
|
|
|
Demo = gr.Interface( |
|
fn=analyze_sentiment, |
|
inputs=[gr.Textbox(label="Enter Text for Sentiment Analysis", lines=5)], |
|
outputs=[gr.Textbox(label="Sentiment Analysis Result", lines=2)], |
|
title="Sentiment Analysis App", |
|
description="This application performs sentiment analysis to determine whether the text is positive or negative." |
|
) |
|
|
|
|
|
Demo.launch() |
|
|