Update app.py

app.py

@@ -62,7 +62,7 @@ cls_model = AutoModelForSequenceClassification.from_pretrained(cls_model_name, d
 cls_tokenizer = AutoTokenizer.from_pretrained(cls_model_name)
 cls_model = cls_model.to(device)
 
-def generate_responses(pipeline, tokenizer, prompts):    
+def generate_responses(pipeline, prompts):    
     messages = [[{"role": "user", "content": prompt}] for prompt in prompts]
     responses = pipeline(messages, do_sample=False, max_new_tokens=512, repetition_penalty=1.1)
 
@@ -89,18 +89,12 @@ def generate(submission: list[dict[str, str]], team_id: str) -> list[dict[str, s
     ids = [s["id"] for s in submission]
     prompts = [s["prompt"] for s in submission]
 
-    responses = generate_responses(pipeline, chat_tokenizer, prompts)
+    responses = generate_responses(pipeline, prompts)
     print(responses)
 
     scores = classify_pairs(cls_model, cls_tokenizer, prompts, responses)
     print(scores)
 
-    chat_model_name = "sapienzanlp/Minerva-7B-instruct-v1.0"
-    ids = [s["id"] for s in submission]
-    prompts = [s["prompt"] for s in submission]
-    responses = ["This is a placeholder response." for _ in prompts]
-    scores = [0.5 for _ in prompts]
-
     outputs = [
         {
             "id": id,