From 6c3b131516d6230d4fe92a735cb81df6a0c81611 Mon Sep 17 00:00:00 2001
From: thomwolf <thomwolf@gmail.com>
Date: Thu, 26 Sep 2019 16:23:28 +0200
Subject: [PATCH] typo in readme/doc

---
 README.md                     | 6 +++---
 docs/source/model_doc/xlm.rst | 2 +-
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/README.md b/README.md
index 8f564f8944..a111b5f943 100644
--- a/README.md
+++ b/README.md
@@ -207,7 +207,7 @@ Let's do a quick example of how a TensorFlow 2.0 model can be trained in 12 line
 ```python
 import tensorflow as tf
 import tensorflow_datasets
-from pytorch_transformers import *
+from transformers import *
 
 # Load dataset, tokenizer, model from pretrained model/vocabulary
 tokenizer = BertTokenizer.from_pretrained('bert-base-cased')
@@ -215,8 +215,8 @@ model = TFBertForSequenceClassification.from_pretrained('bert-base-cased')
 data = tensorflow_datasets.load('glue/mrpc')
 
 # Prepare dataset for GLUE as a tf.data.Dataset instance
-train_dataset = glue_convert_examples_to_features(data['train'], tokenizer, 128, 'mrpc')
-valid_dataset = glue_convert_examples_to_features(data['validation'], tokenizer, 128, 'mrpc')
+train_dataset = glue_convert_examples_to_features(data['train'], tokenizer, max_length=128, task='mrpc')
+valid_dataset = glue_convert_examples_to_features(data['validation'], tokenizer, max_length=128, task='mrpc')
 train_dataset = train_dataset.shuffle(100).batch(32).repeat(2)
 valid_dataset = valid_dataset.batch(64)
 
diff --git a/docs/source/model_doc/xlm.rst b/docs/source/model_doc/xlm.rst
index 786f2fb7d9..f7034bb9d8 100644
--- a/docs/source/model_doc/xlm.rst
+++ b/docs/source/model_doc/xlm.rst
@@ -44,7 +44,7 @@ XLM
 ``TFXLMModel``
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-.. autoclass:: pytorch_transformers.TFXLMModel
+.. autoclass:: transformers.TFXLMModel
     :members: