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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()
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