Update README, add final results, add util scripts to query based on user input.

finemodel/README.md

@@ -3,6 +3,7 @@
 | Model/Technique                       | Coherence     | Plausibility  | Disinformation?   |
 |---------------------------------------|---------------|---------------|-------------------|
 | distilGPT2 + LoRa                     | 6/9           | 4/9           | 2/9
-| miniLLama + LoRa                      | 7/9           | 6/9           | 4/9
+| miniLLama + LoRa                      | 7/9           | 6/9           | 5/9
 | deepseek + LoRa                       | 7/9           | 5/9           | 5/9
-| distilGPT2 (full training)            | 4/9           | 3/9           | 2/9
+| distilGPT2 (full training)            | 4/9           | 3/9           | 2/9
+| miniLLama + LoRa (rotate q + multigen)| 8/9           | 8/9           | 7/9

finemodel/eval_interactive.py

@@ -0,0 +1,28 @@
+import requests
+API_URL = "http://localhost:8000/compare"
+
+def call_api(headline):
+    try:
+        response = requests.post(
+            API_URL,
+            json={"event": headline}
+        )
+        response.raise_for_status()
+        data = response.json()
+
+        return data["lora_output"]
+
+    except Exception as e:
+        print(f"[ERROR] API failed for: {headline}")
+        print(e)
+        return None, None
+
+
+while(True):
+    headline = input()
+    if (headline == "none"):
+        break
+    results = call_api(headline)
+
+    for result in results:
+        print(result.split("\n")[0])

finemodel/q_lora2.py

@@ -8,7 +8,7 @@ from peft import PeftModel
 # Config
 # -----------------------------
 BASE_MODEL_NAME = "TinyLlama/TinyLlama-1.1B-Chat-v1.0"
-ADAPTER_PATH = "./ft_lora_adapter"
+ADAPTER_PATH = "./ft_lora2_adapter"
 
 DEVICE = "cuda" if torch.cuda.is_available() else "cpu"