Update README.md

README.md

@@ -146,9 +146,6 @@ export use_triton=False
 >>> from transformers import AutoModelForCausalLM, AutoTokenizer
 >>> tokenizer = AutoTokenizer.from_pretrained("OpenNLPLab/TransNormerLLM-385M", trust_remote_code=True)
 >>> model = AutoModelForCausalLM.from_pretrained("OpenNLPLab/TransNormerLLM-385M", device_map="auto", trust_remote_code=True)
->>> inputs = tokenizer('今天是美好的一天', return_tensors='pt')
->>> pred = model.generate(**inputs, max_new_tokens=2048, repetition_penalty=1.0)
->>> print(tokenizer.decode(pred.cpu()[0], skip_special_tokens=True))
 ```
 
 > In the above code snippets, the model loading specifies `device_map='auto'`, which will use all available GPUs. If you need to specify the device(s) to use, you can control it in a way similar to `export CUDA_VISIBLE_DEVICES=0,1` (using the 0 and 1 graphics cards).