new model#

app.py

@@ -3,7 +3,7 @@ from evaluations.repo_evaluations import evaluate
 from evaluations.models import RemoteLLM
 import requests
 
-model = RemoteLLM("codellama/CodeLlama-7b-Instruct-hf")
+model = RemoteLLM("meta-llama/Llama-3.1-8B-Instruct")
 
 st.write("\n")
 st.write("Welcome to the online reproducibility evaluation tool!")

evaluations/models.py

@@ -25,10 +25,12 @@ class LocalLLM():
 class RemoteLLM():
   def __init__(self, model_name):
     token = os.getenv("hfToken")
-    self.client = InferenceClient(model_name, token=f"Bearer {token}")
+    self.model_name = model_name
+    self.client = InferenceClient(api_key=token)
 
   def predict(self, response_type, prompt):
     for message in self.client.chat_completion(
+        model=self.model_name,
         messages=[{"role": "system", "content": system_messages[response_type]}, 
                   {"role": "user", "content": prompt}],
         max_tokens=500,

midl.py

@@ -5,9 +5,8 @@ from dotenv import load_dotenv
 load_dotenv() 
 token = os.getenv("githubToken")
 
-
 # Load model directly
+model = LocalLLM("meta-llama/Llama-3.1-8B-Instruct")
 
-model = LocalLLM("codellama/CodeLlama-7b-Instruct-hf")
 res = midl_evaluations(model)
 res.to_csv("results_midl.csv", sep="\t", index=False)