Fill-Mask
Transformers
PyTorch
Japanese
luke
named entity recognition
entity typing
relation classification
question answering
Instructions to use studio-ousia/luke-japanese-base-lite with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use studio-ousia/luke-japanese-base-lite with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="studio-ousia/luke-japanese-base-lite")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("studio-ousia/luke-japanese-base-lite") model = AutoModelForMaskedLM.from_pretrained("studio-ousia/luke-japanese-base-lite") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c9aebb4191c852d39a7716261a4a8633c2d167ac983abd4a0653228f33352951
- Size of remote file:
- 842 kB
- SHA256:
- d8b73a5e054936c920cf5b7d1ec21ce9c281977078269963beb821c6c86fbff7
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