readme updated

README.md

@@ -18,6 +18,23 @@ Model architecture is similar to bert-medium (8 layers, 8 heads, and 512 hidden
 The details can be found at this paper: 
 https://arxiv.org/...
 
+The following code can be used for model loading and tokenization, example max length (514) can be changed:
+```
+	model = AutoModel.from_pretrained([model_path])
+	#for sequence classification:
+	#model = AutoModelForSequenceClassification.from_pretrained([model_path], num_labels=[num_classes])
+
+	tokenizer = PreTrainedTokenizerFast(tokenizer_file=[file_path])
+	tokenizer.mask_token = "[MASK]"
+	tokenizer.cls_token = "[CLS]"
+	tokenizer.sep_token = "[SEP]"
+	tokenizer.pad_token = "[PAD]"
+	tokenizer.unk_token = "[UNK]"
+	tokenizer.bos_token = "[CLS]"
+	tokenizer.eos_token = "[SEP]"
+	tokenizer.model_max_length = 514
+```
+
 ### BibTeX entry and citation info
 ```bibtex
 @article{}