Instructions to use TomokiFujihara/twhin-bert-base-japanese-offensiveness-estimation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TomokiFujihara/twhin-bert-base-japanese-offensiveness-estimation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TomokiFujihara/twhin-bert-base-japanese-offensiveness-estimation", trust_remote_code=True)# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("TomokiFujihara/twhin-bert-base-japanese-offensiveness-estimation", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 55725c7a4b59ddaf16771f1a5e56f3eab413c54c7fe4f484cd1fe934980d4e7c
- Size of remote file:
- 1.12 GB
- SHA256:
- 1d9730f27abab7ea89c2fbf1a508955da27fe927371e87f31618472325db52fd
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