diff --git a/arch/src/consts.rs b/arch/src/consts.rs
index a3e8e428..32172002 100644
--- a/arch/src/consts.rs
+++ b/arch/src/consts.rs
@@ -1,5 +1,5 @@
 pub const DEFAULT_EMBEDDING_MODEL: &str = "katanemo/bge-large-en-v1.5";
-pub const DEFAULT_INTENT_MODEL: &str = "katanemo/deberta-base-nli";
+pub const DEFAULT_INTENT_MODEL: &str = "katanemo/bart-large-mnli";
 pub const DEFAULT_PROMPT_TARGET_THRESHOLD: f64 = 0.8;
 pub const DEFAULT_HALLUCINATED_THRESHOLD: f64 = 0.1;
 pub const RATELIMIT_SELECTOR_HEADER_KEY: &str = "x-arch-ratelimit-selector";
diff --git a/model_server/app/loader.py b/model_server/app/loader.py
index 0712fce1..0994bf54 100644
--- a/model_server/app/loader.py
+++ b/model_server/app/loader.py
@@ -30,7 +30,7 @@ def get_embedding_model(
 
 
 def get_zero_shot_model(
-    model_name=os.getenv("ZERO_SHOT_MODELS", "katanemo/deberta-base-nli"),
+    model_name=os.getenv("ZERO_SHOT_MODELS", "katanemo/bart-large-mnli"),
 ):
     print("Loading Zero-shot Model...")
 
diff --git a/model_server/app/main.py b/model_server/app/main.py
index 4d2faafd..82bbeb50 100644
--- a/model_server/app/main.py
+++ b/model_server/app/main.py
@@ -189,17 +189,18 @@ async def hallucination(req: HallucinationRequest, res: Response):
     if "arch_messages" in req.parameters:
         req.parameters.pop("arch_messages")
 
-    candidate_labels = [f"{k} is {v}" for k, v in req.parameters.items()]
+    candidate_labels = {f"{k} is {v}": k for k, v in req.parameters.items()}
 
     predictions = classifier(
         req.prompt,
-        candidate_labels=candidate_labels,
+        candidate_labels=list(candidate_labels.keys()),
         hypothesis_template="{}",
         multi_label=True,
     )
 
     params_scores = {
-        k[0]: s for k, s in zip(req.parameters.items(), predictions["scores"])
+        candidate_labels[label]: score
+        for label, score in zip(predictions["labels"], predictions["scores"])
     }
 
     logger.info(