pythainlp.wangchanberta
WangchanBERTa base model: wangchanberta-base-att-spm-uncased 1
We used WangchanBERTa for Thai name tagger task, part-of-speech and subword tokenizer.
If you want to finetune model, You can read https://github.com/vistec-AI/thai2transformers
Speed Benchmark
Function |
Named Entity Recognition |
Part of Speech |
---|---|---|
PyThaiNLP basic function |
89.7 ms |
312 ms |
pythainlp.wangchanberta (CPU) |
9.64 s |
9.65 s |
pythainlp.wangchanberta (GPU) |
8.02 s |
8 s |
Notebook:
Modules
- class pythainlp.wangchanberta.ThaiNameTagger(dataset_name: str = 'thainer', grouped_entities: bool = True)[source]
- get_ner(text: str, tag: bool = False) Union[List[Tuple[str, str]], str] [source]
This function tags named-entitiy from text in IOB format. Powered by wangchanberta from VISTEC-depa AI Research Institute of Thailand
- Parameters
- Returns
a list of tuple associated with tokenized word group, NER tag, and output like html tag (if the parameter tag is specified as True). Otherwise, return a list of tuple associated with tokenized word and NER tag
- Return type
References
- 1
Lowphansirikul L, Polpanumas C, Jantrakulchai N, Nutanong S. WangchanBERTa: Pretraining transformer-based Thai Language Models. arXiv:210109635 [cs] [Internet]. 2021 Jan 23 [cited 2021 Feb 27]; Available from: http://arxiv.org/abs/2101.09635