AllenNLP integration for Shiba: Japanese CANINE model
Project description
Allennlp Integration for Shiba
allennlp-shiab-model is a Python library that provides AllenNLP integration for shiba-model.
SHIBA is an approximate reimplementation of CANINE [1] in raw Pytorch, pretrained on the Japanese wikipedia corpus using random span masking. If you are unfamiliar with CANINE, you can think of it as a very efficient (approximately 4x as efficient) character-level BERT model. Of course, the name SHIBA comes from the identically named Japanese canine.
Installation
Installing the library and dependencies is simple using pip.
pip install allennlp-shiba
Example
This library enables users to specify the in a jsonnet config file. Here is an example of the model in jsonnet config file:
{
"dataset_reader": {
"tokenizer": {
"type": "shiba",
},
"token_indexers": {
"tokens": {
"type": "shiba",
}
},
},
"model": {
"shiba_embedder": {
"type": "basic",
"token_embedders": {
"shiba": {
"type": "shiba",
"eval_model": true,
}
}
}
}
}
Reference
- Joshua Tanner and Masato Hagiwara (2021). SHIBA: Japanese CANINE model. GitHub repository, GitHub.
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