WangchanBERTa base model: wangchanberta base att spm uncased Pretrained RoBERTa BASE model on assorted Thai texts (78.5 GB). The script and documentation can be found at this repository. Model description The architecture of the pretrained model is based on RoBERTa [[Liu et al., 2019]](https://arxiv.org/abs/1907.11692). Intended uses & limitations You can use the pretrained model for masked language modeling (i.e. predicting a mask token in the input text). In addition, we also provide finetuned models for multiclass/multilabel text classification and token classification task. Multiclass text classification wisesight sentiment 4 class text classification task ( positive , neutral , negative , and question ) based on social media posts and tweets. wongnai reivews Users' review rating classification task (scale is ranging from 1 to 5) generated reviews enth : ( review star as label) Generated users' review rating classification task (scale is ranging from 1 to 5). Multilabel text classification prachathai67k Thai topic classification with 12 labels based on news article corpus from prachathai.com. The detail is described in this page. Token classification thainer Named entity recogn…
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