README.md

metadata

title: TruthX Fake News Detector
emoji: 🔍
colorFrom: blue
colorTo: red
sdk: docker
app_file: app.py
pinned: false

TruthX - Fake News Detection

TruthX uses state-of-the-art DistilBERT model to detect fake news articles with high accuracy.

Features

• Real-time Detection: Get instant predictions on news authenticity
• Confidence Score: See the model's confidence level
• Multiple Models: Supports BERT, DistilBERT, and RoBERTa models

How to Use

1. Enter any news article or headline in the text box
2. Click "Submit" to get the prediction
3. View the classification (Real/Fake) with confidence scores

Technical Details

• Model: DistilBERT fine-tuned for fake news detection
• Input: Text up to 512 tokens
• Output: Classification label with probability scores

API Access

You can also access the model programmatically via the Hugging Face Inference API:

import requests

API_URL = "https://api-inference.huggingface.co/models/Ankit74990/TruthX-DISTILBERT"
headers = {"Authorization": "Bearer YOUR_TOKEN"}

def query(text):
    response = requests.post(API_URL, headers=headers, json={"inputs": text})
    return response.json()

result = query("Your news text here")

Model Card

This space uses the TruthX-DISTILBERT model.