From 46901b07bef2d4f75565335e44153e8a18623e5c Mon Sep 17 00:00:00 2001
From: KP <109694228@qq.com>
Date: Tue, 6 Apr 2021 11:24:26 +0800
Subject: [PATCH] Fix module doc typo.

---
 demo/senta/README.md | 9 ++++-----
 1 file changed, 4 insertions(+), 5 deletions(-)

diff --git a/demo/senta/README.md b/demo/senta/README.md
index 4ede5c53..d56a8917 100644
--- a/demo/senta/README.md
+++ b/demo/senta/README.md
@@ -51,7 +51,8 @@ $ sh run_finetune.sh
 
 ```python
 module = hub.Module(name="senta_bilstm")
-inputs, outputs, program = module.context(trainable=True, max_seq_len=96)
+inputs, outputs, program = module.context(
+    trainable=True, max_seq_len=128)
 ```
 
 其中最大序列长度`max_seq_len`是可以调整的参数，根据任务文本长度不同可以调整该值。
@@ -92,10 +93,10 @@ tokenizer = hub.CustomTokenizer(
 
 ### Step3: 准备数据集
 ```python
-dataset = hub.dataset.LCQMC(tokenizer=tokenizer, max_seq_len=128)
+dataset = hub.dataset.ChnSentiCorp(tokenizer=tokenizer, max_seq_len=128)
 ```
 
-`hub.dataset.LCQMC()` 会自动从网络下载数据集并解压到用户目录下`$HOME/.paddlehub/dataset`目录；
+`hub.dataset.ChnSentiCorp()` 会自动从网络下载数据集并解压到用户目录下`$HOME/.paddlehub/dataset`目录；
 
 `max_seq_len` 需要与Step1中context接口传入的序列长度保持一致；
 
@@ -142,8 +143,6 @@ PaddleHub提供了许多优化策略，如`AdamWeightDecayStrategy`、`ULMFiTStr
 ```python
 sent_feature = outputs["sentence_feature"]
 
-feed_list = [inputs["words"].name]
-
 cls_task = hub.TextClassifierTask(
     dataset=dataset,
     feature=sent_feature,
-- 
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