Add launch.sh and app files

app.py

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+import streamlit as st
+from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline
+from peft import PeftModel
+import torch
+
+@st.cache_resource
+def load_model():
+    base_model = "Qwen/Qwen3-0.6B"
+    adapter_path = "faizabenatmane/Qwen-3-0.6B"
+
+    tokenizer = AutoTokenizer.from_pretrained(base_model)
+
+    base = AutoModelForSequenceClassification.from_pretrained(
+        base_model,
+        num_labels=2,
+        device_map="cpu"
+    )
+
+    model = PeftModel.from_pretrained(base, adapter_path)
+    model = model.merge_and_unload()
+
+    pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
+    return pipe
+
+generator = load_model()
+
+st.title("📰 Fake News Detection")
+text = st.text_area("Enter a statement (news or claim):", height=200)
+
+if st.button("Check"):
+    with st.spinner("Analyzing..."):
+        prompt = f"Determine if the following statement is fake or real:\n\n{text}\n\nAnswer:"
+        output = generator(prompt, max_length=50, do_sample=False)[0]['generated_text']
+        answer = output.split("Answer:")[-1].strip().split()[0]
+
+        st.subheader("Prediction")
+        st.success(f"🧠 The statement is likely: **{answer}**")

launch.sh

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+#!/bin/bash
+pip install -r requirements.txt
+streamlit run app.py --server.port $PORT --server.address 0.0.0.0

requirements.txt

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+streamlit
+transformers
+torch
+peft