Update README.md

README.md

@@ -10,6 +10,8 @@ inference: false
 <!-- Provide a quick summary of what the model is/does. -->
 
 ## 介绍
+Baichuan-13B-Base为Baichuan-13B系列模型中的预训练版本，经过对齐后的模型可见[Baichuan-13B-Chat](https://github.com/baichuan-inc/Baichuan-13B-Chat)。
+
 Baichuan-13B 是由百川智能继 [Baichuan-7B](https://github.com/baichuan-inc/baichuan-7B) 之后开发的包含 130 亿参数的开源可商用的大规模语言模型，在标准的中文和英文 benchmark上均取得同尺寸最好的效果。本次发布包含有预训练 (Baichuan-13B-Base) 和对齐 (Baichuan-13B-Chat) 两个版本。Baichuan-13B 有如下几个特点：
 
   1. **更大尺寸、更多数据**：Baichuan-13B在[Baichuan-7B](https://github.com/baichuan-inc/baichuan-7B) 的基础上进一步扩大参数量到130亿，并且在高质量的语料上训练了1.4万亿tokens，超过LLaMA-13B 40%，是当前开源13B尺寸下训练数据量最多的模型。支持中英双语，使用ALiBi 位置编码，上下文窗口长度为 4096。
@@ -18,6 +20,8 @@ Baichuan-13B 是由百川智能继 [Baichuan-7B](https://github.com/baichuan-inc
   4. **开源免费可商用**：Baichuan-13B不仅对学术研究完全开放，开发者也仅需邮件申请并获得官方商用许可后，即可以免费商用。
 
 ## Introduction
+Baichuan-13B-Base is the pre-training version in the Baichuan-13B series of models, and the aligned model can be found at [Baichuan-13B-Chat](https://github.com/baichuan-inc/Baichuan-13B-Chat).
+
 Baichuan-13B is an open-source, commercially usable large-scale language model developed by Baichuan Intelligence, following [Baichuan-7B](https://github.com/baichuan-inc/baichuan-7B). With 13 billion parameters, it achieves the best performance in standard Chinese and English benchmarks among models of its size. This release includes two versions: pre-training (Baichuan-13B-Base) and alignment (Baichuan-13B-Chat). Baichuan-13B has the following features:
 
   1. **Larger size, more data**: Baichuan-13B further expands the parameter volume to 13 billion based on [Baichuan-7B](https://github.com/baichuan-inc/baichuan-7B), and has trained 1.4 trillion tokens on high-quality corpora, exceeding LLaMA-13B by 40%. It is currently the model with the most training data in the open-source 13B size. It supports both Chinese and English, uses ALiBi position encoding, and has a context window length of 4096.
@@ -26,32 +30,6 @@ Baichuan-13B is an open-source, commercially usable large-scale language model d
   4. **Open-source, free, and commercially usable**: Baichuan-13B is not only fully open to academic research, but developers can also use it for free commercially after applying for and receiving official commercial permission via email.
 
 
-## How to Get Started with the Model
-
-如下是一个使用Baichuan-13B-Base进行1-shot推理的任务，根据作品给出作者名，正确输出为"夜雨寄北->李商隐"
-```python
-from transformers import AutoModelForCausalLM, AutoTokenizer
-
-tokenizer = AutoTokenizer.from_pretrained("baichuan-inc/Baichuan-13B-Base", trust_remote_code=True)
-model = AutoModelForCausalLM.from_pretrained("baichuan-inc/Baichuan-13B-Base", device_map="auto", trust_remote_code=True)
-inputs = tokenizer('登鹳雀楼->王之涣\n夜雨寄北->', return_tensors='pt')
-inputs = inputs.to('cuda:0')
-pred = model.generate(**inputs, max_new_tokens=64,repetition_penalty=1.1)
-print(tokenizer.decode(pred.cpu()[0], skip_special_tokens=True))
-```
-
-The following is a task of performing 1-shot inference using Baichuan-13B-Base, where the author's name is given based on the work, with the correct output being "One Hundred Years of Solitude->Gabriel Garcia Marquez"
-```python
-from transformers import AutoModelForCausalLM, AutoTokenizer
-
-tokenizer = AutoTokenizer.from_pretrained("baichuan-inc/Baichuan-13B-Base", trust_remote_code=True)
-model = AutoModelForCausalLM.from_pretrained("baichuan-inc/Baichuan-13B-Base", device_map="auto", trust_remote_code=True)
-inputs = tokenizer('Hamlet->Shakespeare\nOne Hundred Years of Solitude->', return_tensors='pt')
-inputs = inputs.to('cuda:0')
-pred = model.generate(**inputs, max_new_tokens=64,repetition_penalty=1.1)
-print(tokenizer.decode(pred.cpu()[0], skip_special_tokens=True))
-```
-
 ## Model Details
 
 ### Model Description