Update app.py

app.py

@@ -12,15 +12,18 @@ max_seq_length = 4096
 dtype = None
 load_in_4bit = True
 hf_token = os.getenv("HF_TOKEN")
+current_num = os.getenv("NUM")
 
-pre_models = "dad1909/CyberSentinel-3"
-uploads_models = "CyberSentinel-4"
+print(f"stage ${current_num}")
+
+api = HfApi(token=hf_token)
+models = f"dad1909/CyberSentinel-{current_num}"
 
 print("Starting model and tokenizer loading...")
 
 # Load the model and tokenizer
 model, tokenizer = FastLanguageModel.from_pretrained(
-    model_name=pre_models,
+    model_name=models,
     max_seq_length=max_seq_length,
     dtype=dtype,
     load_in_4bit=load_in_4bit,
@@ -135,6 +138,11 @@ print("Starting training...")
 trainer_stats = trainer.train()
 print("Training completed.")
 
+num = int(current_num)
+num += 1
+
+uploads_models = f"CyberSentinel-{str(num)}"
+
 print("Saving the trained model...")
 model.save_pretrained_merged("model", tokenizer, save_method="merged_16bit")
 print("Model saved successfully.")
@@ -148,5 +156,5 @@ model.push_to_hub_merged(
 )
 print("Model pushed to hub successfully.")
 
-api = HfApi()
-api.pause_space(repo_id="dad1909/CyberCode")
+api.delete_space_variable(repo_id="dad1909/CyberCode", key="NUM")
+api.add_space_variable(repo_id="dad1909/CyberCode", key="NUM", value=str(num))