Update app.py

app.py

@@ -7,24 +7,20 @@ import torch.nn as nn
 import re
 model_path = r'ssocean/NAIP'  
 
-@spaces.GPU
-def init_model():
-    global model, tokenizer
-    model = AutoModelForSequenceClassification.from_pretrained(
-        model_path,
-        num_labels=1,
-        load_in_8bit=True,
-    )
-    tokenizer = AutoTokenizer.from_pretrained(model_path)
-    model.eval()
-    return model, tokenizer
 
-model, tokenizer = init_model()
+global model, tokenizer
+model = AutoModelForSequenceClassification.from_pretrained(
+    model_path,
+    num_labels=1,
+    load_in_8bit=True,
+)
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+model.eval()
+
+
 
 @spaces.GPU
 def predict(title, abstract):
-    global model, tokenizer
-    
     model_device = next(model.parameters()).device
     text = f'''Given a certain paper, Title: {title}\n Abstract: {abstract}. \n Predict its normalized academic impact (between 0 and 1):'''
     inputs = tokenizer(text, return_tensors="pt").to(model_device)