app.py

from transformers import pipeline
import gradio as gr

# Label mapping
human_read = {"LABEL_0": "Negative", "LABEL_1": "Positive"}

# Load model
sentimental = pipeline("text-classification", model="Dmyadav2001/Sentimental-Analysis")

# Prediction function
def predictive_model(texts):
    result = sentimental(texts)
    sentiment = human_read[result[0]["label"]]
    score = result[0]["score"]
    return sentiment, score

# Gradio Interface
interface = gr.Interface(
    fn=predictive_model,
    inputs="text",
    outputs=["text", "number"],
    title="Sentiment-Analysis-App",
    description="Give your text, and my model will predict whether it's Positive or Negative."
)

interface.launch()