
# roberta-base-thai-syllable

## Model Description

This is a RoBERTa model pre-trained on Thai Wikipedia texts, derived from [wangchanberta-base-wiki-syllable](https://huggingface.co/airesearch/wangchanberta-base-wiki-syllable). Character-embeddings are modified to use BertTokenizerFast. You can fine-tune `roberta-base-thai-syllable` for downstream tasks, such as [POS-tagging](https://huggingface.co/KoichiYasuoka/roberta-base-thai-syllable-upos), [dependency-parsing](https://huggingface.co/KoichiYasuoka/roberta-base-thai-syllable-ud-goeswith), and so on.

## How to Use

```py
from transformers import AutoTokenizer,AutoModelForMaskedLM
tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/roberta-base-thai-syllable")
model=AutoModelForMaskedLM.from_pretrained("KoichiYasuoka/roberta-base-thai-syllable")
```


{"language": ["th"], "license": "apache-2.0", "tags": ["thai", "masked-lm", "wikipedia"], "pipeline_tag": "fill-mask", "mask_token": "<mask>", "widget": [{"text": "\u0e41\u0e1c\u0e19\u0e01\u0e19\u0e35\u0e49\u0e01\u0e33\u0e25\u0e31\u0e07<mask>\u0e01\u0e31\u0e1a\u0e04\u0e27\u0e32\u0e21\u0e17\u0e49\u0e32\u0e17\u0e32\u0e22\u0e43\u0e2b\u0e21\u0e48"}]}
transformers pytorch roberta fill-mask thai masked-lm wikipedia th license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #fill-mask #thai #masked-lm #wikipedia #th #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 


# roberta-base-thai-syllable

## Model Description

This is a RoBERTa model pre-trained on Thai Wikipedia texts, derived from wangchanberta-base-wiki-syllable. Character-embeddings are modified to use BertTokenizerFast. You can fine-tune 'roberta-base-thai-syllable' for downstream tasks, such as POS-tagging, dependency-parsing, and so on.

## How to Use




# roberta-base-thai-syllable ## Model Description

This is a RoBERTa model pre-trained on Thai Wikipedia texts, derived from wangchanberta-base-wiki-syllable. Character-embeddings are modified to use BertTokenizerFast. You can fine-tune 'roberta-base-thai-syllable' for downstream tasks, such as POS-tagging, dependency-parsing, and so on. ## How to Use
TAGS
#transformers #pytorch #roberta #fill-mask #thai #masked-lm #wikipedia #th #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 # roberta-base-thai-syllable ## Model Description

This is a RoBERTa model pre-trained on Thai Wikipedia texts, derived from wangchanberta-base-wiki-syllable. Character-embeddings are modified to use BertTokenizerFast. You can fine-tune 'roberta-base-thai-syllable' for downstream tasks, such as POS-tagging, dependency-parsing, and so on. ## How to Use
passage: TAGS
#transformers #pytorch #roberta #fill-mask #thai #masked-lm #wikipedia #th #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
# roberta-base-thai-syllable## Model Description

This is a RoBERTa model pre-trained on Thai Wikipedia texts, derived from wangchanberta-base-wiki-syllable. Character-embeddings are modified to use BertTokenizerFast. You can fine-tune 'roberta-base-thai-syllable' for downstream tasks, such as POS-tagging, dependency-parsing, and so on.## How to Use