fixed spelling

backend.py

@@ -40,7 +40,7 @@ model = AutoModelForCausalLM.from_pretrained(
     model_id,
     device_map="auto",
     torch_dtype= torch.bfloat16 if torch.cuda.is_available() else torch.float32,
-    use_auth_token=True
+    token=True
 )
 # what models will be used by LlamaIndex:
 Settings.embed_model = InstructorEmbedding(model_name="hkunlp/instructor-base")
@@ -54,7 +54,7 @@ Settings.llm  = GemmaLLMInterface(model=model, tokenizer=tokenizer)
 nodes = None
 index = None
 
-@spaces.zeroGPU(duration=90)
+@spaces.GPU(duration=90)
 def initialize_index():
     global nodes, index
     # Reading documents from disk