Instructions to use TomokiFujihara/luke-japanese-base-lite-offensiveness-estimation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TomokiFujihara/luke-japanese-base-lite-offensiveness-estimation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TomokiFujihara/luke-japanese-base-lite-offensiveness-estimation", trust_remote_code=True)# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("TomokiFujihara/luke-japanese-base-lite-offensiveness-estimation", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 285ac9e17f8eb11c50c2e176e3d23710a52048b486b84c49afd3fb2584f3af45
- Size of remote file:
- 532 MB
- SHA256:
- 63c3389d4b0f0650fc41ec64abf8fcecc9b70a7deaad8cf5215dbbdbc983b25a
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