app.py

import sklearn
import gradio as gr
import joblib

pipe = joblib.load("./pipeline.pkl")
inputs = [gr.Textbox(value = "I love this!")]
outputs = [gr.Label(label = "Sentiment")]
title = "Sentiment Analysis Classifier"
description = "This is a sentiment classifier using longformer model with a logistic regression head. "
def infer(inputs):
    predictions = pipe.predict_proba([inputs])
    label = {
                  "negative":str(predictions[0][0]),
                  "positive":str(predictions[0][1]),
              }
    return label
gr.Interface(infer, inputs = inputs, outputs = outputs, title = title, description = description).launch()