Update qa_summary.py

qa_summary.py

@@ -2,20 +2,22 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
 
 
 def generate_answer(llm_name, texts, query, mode='validate'):
-
+    
     if llm_name == 'solar':
         tokenizer = AutoTokenizer.from_pretrained("Upstage/SOLAR-10.7B-Instruct-v1.0", use_fast=True)
         llm_model = AutoModelForCausalLM.from_pretrained(
         "Upstage/SOLAR-10.7B-Instruct-v1.0",
         device_map="auto", #device_map="cuda"
-        #torch_dtype=torch.float16,)
+        #torch_dtype=torch.float16,
+        )
 
     elif llm_name == 'mistral':
         tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-Instruct-v0.2", use_fast=True)
         llm_model = AutoModelForCausalLM.from_pretrained(
         "mistralai/Mistral-7B-Instruct-v0.2",
         device_map="auto", #device_map="cuda"
-        #torch_dtype=torch.float16,)
+        #torch_dtype=torch.float16,
+        )
 
     elif llm_name == 'phi3mini':
         tokenizer = AutoTokenizer.from_pretrained("microsoft/Phi-3-mini-128k-instruct", use_fast=True)
@@ -23,7 +25,8 @@ def generate_answer(llm_name, texts, query, mode='validate'):
         "microsoft/Phi-3-mini-128k-instruct", 
         device_map="auto", 
         torch_dtype="auto", 
-        trust_remote_code=True,)  
+        trust_remote_code=True,
+        )  
     
     template_texts =""
     for i, text in enumerate(texts):