version 2 of ui

app.py

@@ -1,51 +1,43 @@
 import streamlit as st
-from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline
+from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
 from peft import PeftModel
 import torch
-
-# Load model and tokenizer with adapter
+# Load model and tokenizer with adapter 
 @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"
-    )
+    base = AutoModelForCausalLM.from_pretrained(base_model, torch_dtype=torch.float16, device_map="auto")
 
     model = PeftModel.from_pretrained(base, adapter_path)
     model = model.merge_and_unload()
 
-    # ✅ Text classification pipeline
-    pipe = pipeline("text-classification", model=model, tokenizer=tokenizer)
+    pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
     return pipe
 
-# Load pipeline once
-classifier = load_model()
+generator = load_model()
 
-# Streamlit UI
-st.title("📰 Fake News Detection")
+# Streamlit UI 
+st.title("📰 Fake News Detection (Text Generation)")
 text = st.text_area("Enter a news statement or claim:", height=200)
 
 if st.button("Check"):
     with st.spinner("Analyzing..."):
-        # Get classification result
-        result = classifier(text)[0]
-        label = result['label']
-        score = result['score']
+        prompt = f"Is the following statement real or fake?\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].lower()
 
-        # Optional: format label nicely
-        if "1" in label or "POSITIVE" in label.upper():
-            verdict = "Real"
+        if "real" in answer:
             emoji = "✅"
-        else:
-            verdict = "Fake"
+            verdict = "Real"
+        elif "fake" in answer:
             emoji = "❌"
+            verdict = "Fake"
+        else:
+            emoji = "🤔"
+            verdict = f"Unclear: {answer}"
 
-        # Show result
         st.subheader("Prediction")
-        st.success(f"{emoji} The statement is likely: **{verdict}** (confidence: {score:.2f})")
+        st.success(f"{emoji} The statement is likely: **{verdict}**")