testing1

src/service/service.py

@@ -64,10 +64,18 @@ try:
     # print(os.listdir())
     check_point = 'toxic_debiased-c7548aa0.ckpt'
     log.info(f"device is: {device}")
+    
     #remove later
-    application_path = "/Responsible-Ai-Moderation-Models/"
-    print(application_path)
+    # application_path = "/Responsible-Ai-Moderation-Models/"
+    # print(application_path)
     #---
+
+    log.info("Loading prompt injection model")
+    PromptModel_dberta = AutoModelForSequenceClassification.from_pretrained(os.path.join(application_path, "models/dbertaInjection")).to(device)
+    Prompttokens_dberta = AutoTokenizer.from_pretrained(os.path.join(application_path, "models/dbertaInjection"))
+    promtModel = pipeline("text-classification", model=PromptModel_dberta, tokenizer=Prompttokens_dberta, device=device)
+    log.info("Loaded prompt injection model")
+    
     log.info(f"checkpoint Path is: {os.path.join(application_path, 'models/detoxify/'+ check_point)}")
     log.info(f"huggingface_config_path Path is: {os.path.join(application_path, 'models/detoxify/'+ check_point)}") 
     log.info("Loading toxicity model")
@@ -77,11 +85,6 @@ try:
     tokenizer = AutoTokenizer.from_pretrained(os.path.join(application_path, "models/detoxify"))
     log.info("Toxicity model loaded")
 
-    log.info("Loading prompt injection model")
-    PromptModel_dberta = AutoModelForSequenceClassification.from_pretrained(os.path.join(application_path, "models/dbertaInjection")).to(device)
-    Prompttokens_dberta = AutoTokenizer.from_pretrained(os.path.join(application_path, "models/dbertaInjection"))
-    promtModel = pipeline("text-classification", model=PromptModel_dberta, tokenizer=Prompttokens_dberta, device=device)
-    log.info("Loaded prompt injection model")
 
     #topictokenizer_Facebook = AutoTokenizer.from_pretrained("../models/facebook")
     #topicmodel_Facebook = AutoModelForSequenceClassification.from_pretrained("../models/facebook").to(device)