Update README.md

README.md

@@ -34,7 +34,8 @@ tags:
 
 *Image drawn by GPT-4 DALL·E 3* TL;DR: Perhaps better than all existing models < 70B, in most quantitative evaluations...
 
-# CausalLM 14B
+# CausalLM 14B - Fully Compatible with Meta LLaMA 2
+Use the transformers library that does not require remote/external code to load the model, AutoModelForCausalLM and AutoTokenizer (or manually specify LlamaForCausalLM to load LM, GPT2Tokenizer to load Tokenizer), and model quantization is fully compatible with GGUF (llama.cpp), GPTQ, and AWQ.
 
 **llama.cpp GGUF models**
 GPT2Tokenizer fixed by [Kerfuffle](https://github.com/KerfuffleV2) on [https://github.com/ggerganov/llama.cpp/pull/3743](https://github.com/ggerganov/llama.cpp/pull/3743), new models are now reuploaded.
@@ -106,7 +107,8 @@ We are currently unable to produce accurate benchmark templates for non-QA tasks
 
 *JCommonsenseQA benchmark result is very, very close to [Japanese Stable LM Gamma 7B (83.47)](https://github.com/Stability-AI/lm-evaluation-harness/tree/jp-stable), current SOTA Japanese LM. However, our model was not trained on a particularly large amount of text in Japanese. This seems to reflect the cross-language transferability of metalinguistics.*
 
-# 中文说明
+# 因果语言模型 14B - 与 Meta LLaMA 2 完全兼容
+使用无需远程/外部代码的transformers库加载模型，AutoModelForCausalLM和AutoTokenizer（或者手动指定LlamaForCausalLM加载LM， GPT2Tokenizer加载Tokenizer），并且模型量化与GGUF（llama.cpp）、GPTQ、AWQ完全兼容。
 
 **llama.cpp GGUF models**
 GPT2Tokenizer 支持由 [Kerfuffle](https://github.com/KerfuffleV2) 修复于 [https://github.com/ggerganov/llama.cpp/pull/3743](https://github.com/ggerganov/llama.cpp/pull/3743)，新模型稍后上传。