Added my Project App and Files

app.py

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+import streamlit as st
+import transformers
+import torch
+import requests
+from PIL import Image
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+
+# Setting the page configurations
+st.set_page_config(
+    page_title="Fake News Detection App", 
+    page_icon="fas fa-exclamation-triangle", 
+    layout="wide", 
+    initial_sidebar_state="auto")
+
+# Load the model and tokenizer
+model_name = AutoModelForSequenceClassification.from_pretrained("ikoghoemmanuell/finetuned_fake_news_roberta")
+tokenizer_name = AutoTokenizer.from_pretrained("ikoghoemmanuell/finetuned_fake_news_roberta")
+
+
+# Define the CSS style for the app
+st.markdown(
+"""
+<style>
+body {
+    background-color: #f5f5f5;
+}
+h1 {
+    color: #4e79a7;
+}
+</style>
+""",
+unsafe_allow_html=True
+)
+
+# Set up sidebar
+st.sidebar.header('Navigation')
+menu = ['Home', 'About']
+choice = st.sidebar.selectbox(
+    "Select an option", 
+    menu)
+
+# Define the function for detecting fake news
+@st.cache_resource
+def detect_fake_news(text):
+    # Load the pipeline.
+    pipeline = transformers.pipeline("text-classification", 
+                                     model=model_name, 
+                                     tokenizer=tokenizer_name)
+
+    # Predict the sentiment.
+    prediction = pipeline(text)
+    sentiment = prediction[0]["label"]
+    score = prediction[0]["score"]
+
+    return sentiment, score
+
+    
+# Home section
+if choice == 'Home':
+    st.markdown("<h1 style='text-align: center;margin-top:0px;'>TRUTH- A fake news detection app</h1>", 
+                unsafe_allow_html=True)
+
+    # Loading GIF
+    gif_url = "https://thumbs.gfycat.com/AnchoredWeeklyGreatwhiteshark-size_restricted.gif"
+    st.image(gif_url, 
+             use_column_width=True, 
+             width=400)
+    
+    st.markdown("<h1 style='text-align: center;'>Welcome</h1>", 
+                unsafe_allow_html=True)
+    st.markdown("<p style='text-align: center;'>This is a Fake News Detection App.</p>", 
+                unsafe_allow_html=True)
+    
+    # Get user input
+    text = st.text_input("Enter some text and we'll tell you if it's likely to be fake news or not!")
+    
+    if st.button('Predict'):
+        # Show fake news detection output
+        if text:
+            with st.spinner('Checking if news is Fake...'):
+                label, score = detect_fake_news(text)
+                if label == "LABEL_1":
+                    st.error(f"The text is likely to be fake news with a confidence score of {score*100:.2f}%!")
+                else:
+                    st.success(f"The text is likely to be genuine with a confidence score of {score*100:.2f}%!")
+        else:
+            with st.spinner('Checking if news is Fake...'):
+                st.warning("Please enter some text to detect fake news.")
+
+
+# About section
+if choice == 'About':
+    # Load the banner image
+    banner_image_url = "https://docs.gato.txst.edu/78660/w/2000/a_1dzGZrL3bG/fake-fact.jpg"
+ 
+    # Display the banner image
+    st.image(
+        banner_image_url, 
+        use_column_width=True, 
+        width=400)
+    st.markdown('''
+                    <p style='font-size: 20px; font-style: italic;font-style: bold;'>
+                        
+                        TRUTH is a cutting-edge application specifically designed to combat the spread of fake 
+                        news. Using state-of-the-art algorithms and advanced deep learning techniques, our app 
+                        empowers users to detect and verify the authenticity of news articles. TRUTH provides 
+                        accurate assessments of the reliability of news content. With its user-friendly 
+                        interface and intuitive design, the app enables users to easily navigate and obtain 
+                        trustworthy information in real-time. With TRUTH, you can take control of the news you
+                        consume and make informed decisions based on verified facts.
+                        
+                    </p>
+                ''', 
+                unsafe_allow_html=True)

requirements.txt

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+torch
+transformers