app.py

# -*- coding: utf-8 -*-
"""demo.ipynb

Automatically generated by Colab.

Original file is located at
    https://colab.research.google.com/drive/19sodc0ANzqRgZ0VzMGXr4YQ3fvUvxyjv
"""



# Use a pipeline as a high-level helper
from transformers import pipeline

sentiment_analysis = pipeline("text-classification", model="avichr/heBERT_sentiment_analysis")
def analyze_sentiment(text):
    results = sentiment_analysis(text)
    for result in results:
        print(f"Label: {result['label']}, Score: {result['score']}")

texts = [
    "Worst rental I ever got"
    "I really enjoyed my stay !"

]

analyze_sentiment(texts)



import gradio as gr
from transformers import pipeline



interface = gr.Interface(
    fn=analyze_sentiment,
    inputs=gr.Textbox(lines=2, placeholder="Enter your review or statement here..."),
    outputs=[
        gr.Textbox(label="Sentiment"),
        gr.Number(label="Score")
    ],
    title="Sentiment Analysis Score"
)


interface.launch()