readme updated

README.md

@@ -15,8 +15,12 @@ The pretrained corpus is OSCAR's Turkish split, but it is further filtered and c
 
 Model architecture is similar to bert-medium (8 layers, 8 heads, and 512 hidden size). Tokenization algorithm is Character-level, which means that text is split by individual characters. Vocabulary size is 16.7k. 
 
-## Note that this model does not include a tokenizer file, because it uses ByT5Tokenizer. The following code can be used for tokenization, example max length(1024) can be changed:
+## Note that this model does not include a tokenizer file, because it uses ByT5Tokenizer. The following code can be used for model loading and tokenization, example max length(1024) can be changed:
 ```
+	model = AutoModel.from_pretrained([model_path])
+	#for sequence classification:
+	#model = AutoModelForSequenceClassification.from_pretrained([model_path], num_labels=[num_classes])
+
 	tokenizer = ByT5Tokenizer.from_pretrained("google/byt5-small")
 	tokenizer.mask_token = tokenizer.special_tokens_map_extended['additional_special_tokens'][0]
 	tokenizer.cls_token = tokenizer.special_tokens_map_extended['additional_special_tokens'][1]