potential cuda-xgb conflicts

app.py

@@ -4,7 +4,6 @@ import os
 import pandas as pd
 from transformers import AutoModelForCausalLM, AutoTokenizer
 import torch
-import xgboost as xgb
 import pandas as pd
 import numpy as np
 import torch
@@ -22,6 +21,12 @@ theme = gr.Theme.from_hub("gstaff/xkcd")
 @spaces.GPU
 def detect_ai_text(text):
     global loaded
+
+    import xgboost as xgb
+    model_path = Path(__file__).parent / "model.json"
+    model = xgb.XGBClassifier()
+    model.load_model(model_path)
+
     if not loaded:
         return "❗ Model not loaded. We require a GPU to run DivEye.", 0.0, pd.DataFrame({
             "Source": ["AI Generated", "Human Written"],
@@ -41,7 +46,7 @@ def detect_ai_text(text):
 
     # Call software
     # ===========================================================
-    global model, div_model, div_tokenizer, bi_model, bi_tokenizer
+    global div_model, div_tokenizer, bi_model, bi_tokenizer
 
     # =====================================================================
     # DivEye features
@@ -153,10 +158,7 @@ if torch.cuda.is_available():
 
     div_model.eval()
     bi_model.eval()
-    
-    model_path = Path(__file__).parent / "model.json"
-    model = xgb.XGBClassifier()
-    model.load_model(model_path)
+
 
 # Gradio app setup
 with gr.Blocks(title="DivEye") as demo: