Instructions to use uzabase/luke-japanese-wordpiece-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use uzabase/luke-japanese-wordpiece-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="uzabase/luke-japanese-wordpiece-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("uzabase/luke-japanese-wordpiece-base") model = AutoModelForMaskedLM.from_pretrained("uzabase/luke-japanese-wordpiece-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 439 Bytes
4117b7f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | {
"additional_special_tokens": [
{
"content": "<ent>",
"lstrip": false,
"normalized": true,
"rstrip": false,
"single_word": false
},
{
"content": "<ent2>",
"lstrip": false,
"normalized": true,
"rstrip": false,
"single_word": false
}
],
"cls_token": "[CLS]",
"mask_token": "[MASK]",
"pad_token": "[PAD]",
"sep_token": "[SEP]",
"unk_token": "[UNK]"
}
|