Token Classification
Transformers
Safetensors
Japanese
bert
japanese
koyobun
orthography
kanji-kana
government-writing
Eval Results (legacy)
Instructions to use NagaYu/scribe-usage-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NagaYu/scribe-usage-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="NagaYu/scribe-usage-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("NagaYu/scribe-usage-classifier") model = AutoModelForTokenClassification.from_pretrained("NagaYu/scribe-usage-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dacdb5ce86b2664a490b7dbb39c176f62d9f46a4a8b4df8b74ba3794d0a03719
- Size of remote file:
- 5.2 kB
- SHA256:
- 631c3506af9594859ac253f6468c1414de3871737ff8df957af648cdae2a2b64
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