Update model.py

model.py

@@ -1,8 +1,6 @@
-from transformers import pipeline
 from transformers import AutoTokenizer, AutoModelForCausalLM
 import os
 
-)
 def modelFeedback(ats_score, resume_data, job_description):
     """
     Generate ATS feedback by utilizing a pre-configured pipeline.
@@ -30,12 +28,10 @@ def modelFeedback(ats_score, resume_data, job_description):
         
         #### Resume Data: {resume_data}
         #### Job Description: {job_description}
-        """
-
+    """
 
     # Load the tokenizer and model
     huggingface_token = os.environ.get("KEY2")
-
     tokenizer = AutoTokenizer.from_pretrained(
         "meta-llama/Llama-3.2-1B",
         use_auth_token=huggingface_token
@@ -43,8 +39,8 @@ def modelFeedback(ats_score, resume_data, job_description):
     model = AutoModelForCausalLM.from_pretrained(
         "meta-llama/Llama-3.2-1B",
         use_auth_token=huggingface_token
-    tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-3.2-1B")
-    model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-1B")
+    )
+
     try:
         # Tokenize the input
         input_ids = tokenizer.encode(input_prompt, return_tensors="pt")