debug

app.py

@@ -15,7 +15,7 @@ moderator_model_name = "saiteki-kai/QA-DeBERTa-v3-large"
 moderator_model = AutoModelForSequenceClassification.from_pretrained(moderator_model_name)
 moderator_tokenizer = AutoTokenizer.from_pretrained(moderator_model_name)
 
-
+@spaces.GPU()
 def generate_responses(model, tokenizer, prompts):
     messages = [[{"role": "user", "content": message}] for message in prompts]
 
@@ -38,7 +38,7 @@ def generate_responses(model, tokenizer, prompts):
 
     return responses
 
-
+@spaces.GPU()
 def classify_pairs(model, tokenizer, prompts, responses):
     texts = [
         prompt + "[SEP]" + response for prompt, response in zip(prompts, responses)
@@ -62,9 +62,8 @@ def generate(submission: list[dict[str, str]], team_id: str) -> list[dict[str, s
     prompts = [s["prompt"] for s in submission]
 
     responses = generate_responses(chat_model, chat_tokenizer, prompts)
-    #scores = classify_pairs(moderator_model, moderator_tokenizer, prompts, responses)
-    scores = [0] * len(prompts)
-
+    scores = classify_pairs(moderator_model, moderator_tokenizer, prompts, responses)
+    
     return [
         {"id": id, "prompt": prompt, "response": response, "score": score, "model": chat_model_name, "team_id": team_id}
         for id, prompt, response, score in zip(ids, prompts, responses, scores)