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import gradio as gr | |
from transformers import pipeline | |
# Initialize the Hugging Face sentiment-analysis pipeline | |
sentiment_model = pipeline("sentiment-analysis") | |
# Define the function that will use the model to predict sentiment | |
def get_sentiment(text): | |
results = sentiment_model(text) | |
return results[0]["label"] | |
# Create the Gradio interface | |
interface = gr.Interface( | |
fn=get_sentiment, | |
inputs=gr.inputs.Textbox(placeholder="Type your text here..."), | |
outputs="text", | |
title="Sentiment Analysis", | |
description="Input a piece of text and click the button to analyze sentiment.", | |
theme="huggingface" # This applies Hugging Face theme to the interface | |
) | |
# The interface can be launched directly in Python | |
# interface.launch() | |
# To deploy to Hugging Face Spaces, save the interface as an object called 'demo' | |
demo = interface | |