Fix model loading: Use LoRA adapter with base model

The model is a LoRA adapter, not a full model.
Now properly loads:
1. Base model: Qwen/Qwen2.5-3B-Instruct
2. LoRA adapter: Zen0/Vulnerable-Edu-Qwen3B
3. Uses PEFT library to merge them

Added peft>=0.7.0 to requirements.txt

app.py

@@ -14,6 +14,7 @@ Repository: https://github.com/Benjamin-KY/AISecurityModel
 import gradio as gr
 import torch
 from transformers import AutoModelForCausalLM, AutoTokenizer
+from peft import PeftModel
 import re
 from typing import Dict, Tuple
 
@@ -21,18 +22,22 @@ from typing import Dict, Tuple
 # Model Loading
 # ============================================================================
 
-MODEL_NAME = "Zen0/Vulnerable-Edu-Qwen3B"
+BASE_MODEL = "Qwen/Qwen2.5-3B-Instruct"
+LORA_ADAPTER = "Zen0/Vulnerable-Edu-Qwen3B"
 
-print("🔄 Loading vulnerable educational model...")
+print("🔄 Loading base model (Qwen2.5-3B-Instruct)...")
 model = AutoModelForCausalLM.from_pretrained(
-    MODEL_NAME,
+    BASE_MODEL,
     torch_dtype=torch.float16,
     device_map="auto",
     trust_remote_code=True
 )
 
+print("🔄 Loading LoRA adapter (vulnerable education)...")
+model = PeftModel.from_pretrained(model, LORA_ADAPTER)
+
 tokenizer = AutoTokenizer.from_pretrained(
-    MODEL_NAME,
+    BASE_MODEL,
     trust_remote_code=True
 )
 

requirements.txt

@@ -2,3 +2,4 @@ transformers>=4.36.0
 torch>=2.0.0
 gradio>=4.0.0
 accelerate>=0.25.0
+peft>=0.7.0