pythainlp.wangchanberta
The pythainlp.wangchanberta module is built upon the WangchanBERTa base model, specifically the wangchanberta-base-att-spm-uncased model, as detailed in the paper by Lowphansirikul et al. [1].
This base model is utilized for various natural language processing tasks in the Thai language, including named entity recognition, part-of-speech tagging, and subword tokenization.
If you intend to fine-tune the model or explore its capabilities further, please refer to the thai2transformers repository.
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 |
For a comprehensive performance benchmark, the following notebooks are available: