Update README.md

README.md

@@ -34,10 +34,6 @@ tags:
 
 *Image drawn by GPT-4 DALL·E 3* TL;DR: Perhaps this 7B model, better than all existing models <= 33B, in most quantitative evaluations...
 
-# Please Stop Using WRONG unofficial quant models unless you know what you're doing
-
-GPTQ quants require a good dataset for calibration, and the default C4 dataset is not capable.
-
 **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 reuploaded.
 
@@ -72,7 +68,7 @@ other ACC: 70.04
 
 social ACC: 72.41 
 
-**AVERAGE ACC:63.82** (Outperforms / Equal to the best Mistral-7B Chat-style fine-tunes, and ALL other models under 33B.)
+**AVERAGE ACC:63.82** (Outperforms / Equal to the best Mistral-7B Chat-style fine-tunes, ChatGLM3-6B and ALL other models under 33B.)
 
 ## CEval (Val):
 STEM acc: 61.67
@@ -85,7 +81,7 @@ Other acc: 68.35
 
 Hard acc:48.03
 
-**AVERAGE acc:70.27** (Outperforms ALL 7B models currently.)
+**AVERAGE acc:70.27** (Outperforms ALL 7B models currently, including ChatGLM3-6B.)
 
 ## GSM8K
 
@@ -126,7 +122,7 @@ STEM准确率：56.83
 
 社会学准确率：72.41
 
-**平均准确率：63.82** （优于/平于最好的 Mistral-7B 聊天格式的微调，和其余的33B及以下模型。）
+**平均准确率：63.82** （优于/平于最好的 Mistral-7B 聊天格式的微调，ChatGLM3-6B 和其余的33B及以下模型。）
 
 ## CEval（验证集）：
 STEM准确率：61.67
@@ -139,7 +135,7 @@ STEM准确率：61.67
 
 困难准确率：48.03
 
-**平均准确率：70.27** （优于当前所有7B模型。）
+**平均准确率：70.27** （优于当前所有7B模型，包括 ChatGLM3-6B）
 
 ## GSM8K