initial release

README.md

@@ -1,3 +1,26 @@
----
-license: apache-2.0
----
+---
+language:
+- "th"
+tags:
+- "thai"
+- "masked-lm"
+- "wikipedia"
+license: "apache-2.0"
+pipeline_tag: "fill-mask"
+mask_token: "<mask>"
+---
+
+# roberta-base-thai-char
+
+## Model Description
+
+This is a RoBERTa model pre-trained on Thai Wikipedia texts with character-wise embeddings to use BertTokenizerFast. You can fine-tune `roberta-base-thai-char` for downstream tasks, such as [POS-tagging](https://huggingface.co/KoichiYasuoka/roberta-base-thai-char-upos), dependency-parsing, and so on.
+
+## How to Use
+
+```py
+from transformers import AutoTokenizer,AutoModelForMaskedLM
+tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/roberta-base-thai-char")
+model=AutoModelForMaskedLM.from_pretrained("KoichiYasuoka/roberta-base-thai-char")
+```
+