Update README.md

README.md

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 This is the LLaMAfied version of [Qwen/Qwen-7B-Chat](https://huggingface.co/Qwen/Qwen-7B-Chat), recalibrated to fit the original LLaMA/LLaMA-2-like model structure.
 
-You can use LlamaForCausalLM for model inference, which is the same as LLaMA/LLaMA-2 models (the tokenizer remains the same, so you still need to allow external codes when loading, eg: `AutoTokenizer.from_pretrained(llama_model_path, use_fast=False, trust_remote_code=True)`).
+You can use LlamaForCausalLM for model inference, which is the same as LLaMA/LLaMA-2 models (using GPT2Tokenizer converted from the original tiktoken, by [vonjack](https://huggingface.co/vonjack)).
 
 The model has been edited to be white-labelled, meaning the model will no longer call itself a Qwen.
 
@@ -27,7 +27,7 @@ Issue: Compared to the original Qwen-Chat scoring 53.9, the MMLU score dropped s
 
 这是 [通义千问 Qwen/Qwen-7B-Chat](https://huggingface.co/Qwen/Qwen-7B-Chat) 的 LLaMA 化版本，经过重新校准以适应原始的类似 LLaMA/LLaMA-2 的模型结构。
 
-您可以使用 LlamaCausalLM 进行模型推理，和 LLaMA/LLaMA-2 保持一致（分词器保持不变，因此加载时仍然需要允许外部代码，例如：`AutoTokenizer.from_pretrained(llama_model_path, use_fast=False, trust_remote_code=True)`）。
+您可以使用 LlamaCausalLM 进行模型推理，和 LLaMA/LLaMA-2 保持一致（使用由 [vonjack](https://huggingface.co/vonjack) 从原始 tiktoken 转换而来的 GPT2Tokenizer 分词器）。
 
 模型已经被编辑实现白标化，不再自称通义千问。