From 93b1420ee9e4a86e0faf8d6a14e7c80fb41311cb Mon Sep 17 00:00:00 2001
From: ZHU QIHAO <18811325956@163.com>
Date: Mon, 27 Nov 2023 21:48:38 +0800
Subject: [PATCH] Update README.md

---
 README.md | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/README.md b/README.md
index fc0bbb6..d0241a5 100644
--- a/README.md
+++ b/README.md
@@ -74,7 +74,7 @@ Here are some examples of how to use our model.
 from transformers import AutoTokenizer, AutoModelForCausalLM
 import torch
 tokenizer = AutoTokenizer.from_pretrained("deepseek-ai/deepseek-coder-6.7b-base", trust_remote_code=True)
-model = AutoModelForCausalLM.from_pretrained("deepseek-ai/deepseek-coder-6.7b-base", trust_remote_code=True).cuda()
+model = AutoModelForCausalLM.from_pretrained("deepseek-ai/deepseek-coder-6.7b-base", trust_remote_code=True, torch_dtype=torch.bfloat16).cuda()
 input_text = "#write a quick sort algorithm"
 inputs = tokenizer(input_text, return_tensors="pt").to(model.device)
 outputs = model.generate(**inputs, max_length=128)
@@ -101,7 +101,7 @@ def quick_sort(arr):
 from transformers import AutoTokenizer, AutoModelForCausalLM
 import torch
 tokenizer = AutoTokenizer.from_pretrained("deepseek-ai/deepseek-coder-6.7b-base", trust_remote_code=True)
-model = AutoModelForCausalLM.from_pretrained("deepseek-ai/deepseek-coder-6.7b-base", trust_remote_code=True).cuda()
+model = AutoModelForCausalLM.from_pretrained("deepseek-ai/deepseek-coder-6.7b-base", trust_remote_code=True, torch_dtype=torch.bfloat16).cuda()
 input_text = """<｜fim▁begin｜>def quick_sort(arr):
     if len(arr) <= 1:
         return arr
@@ -127,7 +127,7 @@ This code will output the following result:
 ```python
 from transformers import AutoTokenizer, AutoModelForCausalLM
 tokenizer = AutoTokenizer.from_pretrained("deepseek-ai/deepseek-coder-6.7b-instruct", trust_remote_code=True)
-model = AutoModelForCausalLM.from_pretrained("deepseek-ai/deepseek-coder-6.7b-instruct", trust_remote_code=True).cuda()
+model = AutoModelForCausalLM.from_pretrained("deepseek-ai/deepseek-coder-6.7b-instruct", trust_remote_code=True, torch_dtype=torch.bfloat16).cuda()
 messages=[
     { 'role': 'user', 'content': "write a quick sort algorithm in python."}
 ]
@@ -175,7 +175,7 @@ You are an AI programming assistant, utilizing the DeepSeek Coder model, develop
 ```python
 from transformers import AutoTokenizer, AutoModelForCausalLM
 tokenizer = AutoTokenizer.from_pretrained("deepseek-ai/deepseek-coder-6.7b-base", trust_remote_code=True)
-model = AutoModelForCausalLM.from_pretrained("deepseek-ai/deepseek-coder-6.7b-base", trust_remote_code=True).cuda()
+model = AutoModelForCausalLM.from_pretrained("deepseek-ai/deepseek-coder-6.7b-base", trust_remote_code=True, torch_dtype=torch.bfloat16).cuda()
 
 input_text = """#utils.py
 import torch