Update README.md

README.md

@@ -10,12 +10,14 @@ LayoutLM is a simple but effective pre-training method of text and layout for do
 [LayoutLM: Pre-training of Text and Layout for Document Image Understanding](https://arxiv.org/abs/1912.13318)
 Yiheng Xu, Minghao Li, Lei Cui, Shaohan Huang, Furu Wei, Ming Zhou, [KDD 2020](https://www.kdd.org/kdd2020/accepted-papers)
 
-## Training data
-
-We pre-train LayoutLM on IIT-CDIP Test Collection 1.0\* dataset with two settings. 
-
-* LayoutLM-Base, Uncased (11M documents, 2 epochs): 12-layer, 768-hidden, 12-heads, 113M parameters **(This Model)**
-* LayoutLM-Large, Uncased (11M documents, 2 epochs): 24-layer, 1024-hidden, 16-heads, 343M parameters
+## Different Tokenizer
+Note that LayoutLM-Cased requires a different tokenizer, based on RobertaTokenizer. You can
+initialize it as follows:
+
+~~~
+from transformers import AutoTokenizer
+tokenizer = AutoTokenizer.from_pretrained('microsoft/layoutlm-base-cased') 
+~~~
 
 ## Citation