Update README.md

README.md

@@ -30,28 +30,34 @@ Baichuan-13B is an open-source, commercially available large-scale language mode
 
 ## How to Get Started with the Model
 
-如下是一个使用Baichuan-13B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"
+如下是一个使用Baichuan-13B-Chat进行对话的示例，正确输出为"乔戈里峰。世界第二高峰———乔戈里峰西方登山者称其为k2峰，海拔高度是8611米，位于喀喇昆仑山脉的中巴边境上"
 ```python
-from transformers import AutoModelForCausalLM, AutoTokenizer
-
-tokenizer = AutoTokenizer.from_pretrained("baichuan-inc/Baichuan-13B", trust_remote_code=True)
-model = AutoModelForCausalLM.from_pretrained("baichuan-inc/Baichuan-13B", 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))
+import torch
+from transformers import AutoModel, AutoTokenizer
+from transformers.generation.utils import GenerationConfig
+tokenizer = AutoTokenizer.from_pretrained("baichuan-inc/Baichuan-13B-Chat", use_fast=False, trust_remote_code=True)
+model = AutoModel.from_pretrained("baichuan-inc/Baichuan-13B-Chat", device_map="auto", torch_dtype=torch.float16, trust_remote_code=True)
+model.generation_config = GenerationConfig.from_pretrained("baichuan-inc/Baichuan-13B-Chat")
+messages = []
+messages.append({"role": "user", "content": "世界上第二高的山峰是哪座"})
+response = model.chat(tokenizer, messages)
+print(response)
 ```
 
-The following is a task of performing 1-shot inference using Baichuan-13B, where the author's name is given based on the work, with the correct output being "One Hundred Years of Solitude->Gabriel Garcia Marquez"
+```
+
+Here is an example of a conversation using Baichuan-13B-Chat, the correct output is "K2. The world's second highest peak - K2, also known as Mount Godwin-Austen or Chhogori, with an altitude of 8611 meters, is located on the China-Pakistan border in the Karakoram Range."
 ```python
-from transformers import AutoModelForCausalLM, AutoTokenizer
-
-tokenizer = AutoTokenizer.from_pretrained("baichuan-inc/Baichuan-13B", trust_remote_code=True)
-model = AutoModelForCausalLM.from_pretrained("baichuan-inc/Baichuan-13B", 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))
+import torch
+from transformers import AutoModel, AutoTokenizer
+from transformers.generation.utils import GenerationConfig
+tokenizer = AutoTokenizer.from_pretrained("baichuan-inc/Baichuan-13B-Chat", use_fast=False, trust_remote_code=True)
+model = AutoModel.from_pretrained("baichuan-inc/Baichuan-13B-Chat", device_map="auto", torch_dtype=torch.float16, trust_remote_code=True)
+model.generation_config = GenerationConfig.from_pretrained("baichuan-inc/Baichuan-13B-Chat")
+messages = []
+messages.append({"role": "user", "content": "The second highest mountain in the world is K2."})
+response = model.chat(tokenizer, messages)
+print(response)
 ```
 
 ## Model Details