Instructions to use KoichiYasuoka/bert-large-japanese-unidic-luw-upos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KoichiYasuoka/bert-large-japanese-unidic-luw-upos with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="KoichiYasuoka/bert-large-japanese-unidic-luw-upos")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("KoichiYasuoka/bert-large-japanese-unidic-luw-upos") model = AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/bert-large-japanese-unidic-luw-upos", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4d26b71af650747f2fc2796e9a15313ad27ff2ce20e191b4d7c47e950e90dbcc
- Size of remote file:
- 1.4 GB
- SHA256:
- 75194ddfe8031f46c0ef67a763d5afc61f0a45324f20e4d3b64eb099cdceae2f
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