LLM: fix QLoRA finetuning example on CPU (#9489)

python/llm/example/CPU/QLoRA-FineTuning/qlora_finetuning_cpu.py

@@ -25,6 +25,7 @@ from bigdl.llm.transformers.qlora import get_peft_model, prepare_model_for_kbit_
 from bigdl.llm.transformers import AutoModelForCausalLM
 from datasets import load_dataset
 import argparse
+from bigdl.llm.utils.isa_checker import ISAChecker
 
 if __name__ == "__main__":
     parser = argparse.ArgumentParser(description='Predict Tokens using `generate()` API for Llama2 model')
@@ -63,6 +64,11 @@ if __name__ == "__main__":
     model = get_peft_model(model, config)
     tokenizer.pad_token_id = 0
     tokenizer.padding_side = "left"
+    
+    # To avoid only one core is used on client CPU
+    isa_checker = ISAChecker()
+    bf16_flag = isa_checker.check_avx512()
+    
     trainer = transformers.Trainer(
         model=model,
         train_dataset=data["train"],
@@ -73,7 +79,7 @@ if __name__ == "__main__":
             max_steps=200,
             learning_rate=2e-4,
             save_steps=100,
-            bf16=True,
+            bf16=bf16_flag,
             logging_steps=20,
             output_dir="outputs",
             optim="adamw_hf",  # paged_adamw_8bit is not supported yet