Update README.md

README.md

@@ -5,18 +5,24 @@ license: apache-2.0
 
 
 APUS-xDAN-4.0-MOE
+
 Introduction
-APUS-xDAN-4.0-MOE is a transformer-based MoE decoder-only language model pretrained on a large amount of data.
+APUS-xDAN-4.0-MOE is a transformer-based MoE decoder-only language model 对齐在 on a large amount of data.
 
 For more details, please refer to our blog post and GitHub repo.
 
 Model Details
-APUS-xDAN-4.0-MOE employs Mixture of Experts (MoE) architecture, where the models are upcycled from dense language models. For instance, APUS-xDAN-4.0-MOE is upcycled from Qwen-1.8B. It has 14.3B parameters in total and 2.7B activated parameters during runtime, while achieching comparable performance to Qwen1.5-7B, it only requires 25% of the training resources. We also observed that the inference speed is 1.74 times that of Qwen1.5-7B.
+APUS-xDAN-4.0-MOE employs Mixture of Experts (MoE) architecture, where the models are upcycled from dense language models. For instance, APUS-xDAN-4.0-MOE is upcycled from xDAN-L2 Series which are high performance alignModels. It has 136B parameters in total and 30B activated parameters during runtime.
+进过先进量化技术优化，我们的开源版本仅仅只有42GB大小，是可以很好的在消费级显卡例如4090，3090上运行。
+
 
 Requirements
 The code of APUS-xDAN-4.0-MOE has been in the latest Hugging face transformers and we advise you to build from source with command pip install git+https://github.com/huggingface/transformers, or you might encounter the following error:
 
- 
+
+Usage
+llama.cpp
+
 
 License
 APUS-xDAN-4.0-MOE is licensed under the LLAMA 2 Community License, Copyright (c) Meta Platforms, Inc. All Rights Reserved.