From c0e4405cd359f2f56df03fdbe2191ec44904b54e Mon Sep 17 00:00:00 2001
From: yonggie <1156910334@qq.com>
Date: Mon, 1 May 2023 00:04:37 +0800
Subject: [PATCH 1/2] =?UTF-8?q?=E6=9B=B4=E6=AD=A3pipline=E5=88=B0pipeline?=
 =?UTF-8?q?=EF=BC=8C=E6=9B=B4=E6=AD=A3example=EF=BC=8C=E5=8E=9Fexample?=
 =?UTF-8?q?=E6=9C=89typo=EF=BC=8C=E8=B7=91=E4=B8=8D=E9=80=9A?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 .../Erlangshen-Ubert-330M-Chinese.md"                     | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git "a/source/docs/\344\272\214\351\203\216\347\245\236\347\263\273\345\210\227/Erlangshen-Ubert-330M-Chinese.md" "b/source/docs/\344\272\214\351\203\216\347\245\236\347\263\273\345\210\227/Erlangshen-Ubert-330M-Chinese.md"
index 92fe2b5..34f60a0 100644
--- "a/source/docs/\344\272\214\351\203\216\347\245\236\347\263\273\345\210\227/Erlangshen-Ubert-330M-Chinese.md"
+++ "b/source/docs/\344\272\214\351\203\216\347\245\236\347\263\273\345\210\227/Erlangshen-Ubert-330M-Chinese.md"
@@ -49,10 +49,10 @@ Run the code
 
 ```python
 import argparse
-from fengshen import UbertPiplines
+from fengshen import UbertPipelines
 
 total_parser = argparse.ArgumentParser("TASK NAME")
-total_parser = UbertPiplines.piplines_args(total_parser)
+total_parser = UbertPipelines.pipelines_args(total_parser)
 args = total_parser.parse_args()
 
 args.pretrained_model_path = "IDEA-CCNL/Erlangshen-Ubert-330M-Chinese"
@@ -69,7 +69,7 @@ test_data=[
         "id": 0}
 ]
 
-model = UbertPiplines(args)
+model = UbertPipelines(args)
 result = model.predict(test_data)
 for line in result:
     print(line)
@@ -101,7 +101,7 @@ for line in result:
 
 ## 数据预处理示例
 
-整个模型的 Piplines 我们已经写好，所以为了方便，我们定义了数据格式。目前我们在预训练中主要含有一下几种任务类型
+整个模型的 Pipelines 我们已经写好，所以为了方便，我们定义了数据格式。目前我们在预训练中主要含有一下几种任务类型
 
 | task_type | subtask_type   |
 |:---------:|:--------------:|

From e1f9b188ada78af72a868adbdb41ef97b540aca5 Mon Sep 17 00:00:00 2001
From: yonggie <1156910334@qq.com>
Date: Mon, 1 May 2023 14:36:58 +0800
Subject: [PATCH 2/2] =?UTF-8?q?=E4=BF=AE=E6=94=B9example=20typo=EF=BC=8C?=
 =?UTF-8?q?=E5=90=A6=E5=88=99=E6=8A=A5=E9=94=99?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 .../Erlangshen-Ubert-110M-Chinese.md"                     | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git "a/source/docs/\344\272\214\351\203\216\347\245\236\347\263\273\345\210\227/Erlangshen-Ubert-110M-Chinese.md" "b/source/docs/\344\272\214\351\203\216\347\245\236\347\263\273\345\210\227/Erlangshen-Ubert-110M-Chinese.md"
index bc6d82e..731f8bb 100644
--- "a/source/docs/\344\272\214\351\203\216\347\245\236\347\263\273\345\210\227/Erlangshen-Ubert-110M-Chinese.md"
+++ "b/source/docs/\344\272\214\351\203\216\347\245\236\347\263\273\345\210\227/Erlangshen-Ubert-110M-Chinese.md"
@@ -49,10 +49,10 @@ pip install --editable ./
 一键运行下面代码得到预测结果, 你可以任意修改示例 text 和要抽取的 entity_type，体验一下 Zero-Shot 性能
 ```python
 import argparse
-from fengshen import UbertPiplines
+from fengshen import UbertPipelines
 
 total_parser = argparse.ArgumentParser("TASK NAME")
-total_parser = UbertPiplines.piplines_args(total_parser)
+total_parser = UbertPipelines.pipelines_args(total_parser)
 args = total_parser.parse_args()
 args.pretrained_model_path = 'IDEA-CCNL/Erlangshen-Ubert-110M-Chinese'  #预训练模型路径
 test_data=[
@@ -67,7 +67,7 @@ test_data=[
         "id": 0}
 ]
 
-model = UbertPiplines(args)
+model = UbertPipelines(args)
 result = model.predict(test_data)
 for line in result:
     print(line)
@@ -99,7 +99,7 @@ for line in result:
 
 ### 数据预处理示例
 
-整个模型的 Piplines 我们已经写好，所以为了方便，我们定义了数据格式。目前我们在预训练中主要含有一下几种任务类型
+整个模型的 Pipelines 我们已经写好，所以为了方便，我们定义了数据格式。目前我们在预训练中主要含有一下几种任务类型
 
 | task_type | subtask_type   |
 |:---------:|:--------------:|