Instructions to use TomokiFujihara/twhin-bert-large-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-large-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-large-japanese-offensiveness-estimation", trust_remote_code=True)# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("TomokiFujihara/twhin-bert-large-japanese-offensiveness-estimation", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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**Summary**
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| 評価指標 | スコア |
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| F値_NOT |
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| F値_GRY |
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| F値_OFF |
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| マクロ平均F値 |
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| 正解率 |
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**Confusion matrix**
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| 正解ラベル \ 予測結果 | Not Offensive | Gray-area | Offensive |
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**Summary**
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| 評価指標 | スコア |
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| ----- | ----- |
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| F値_NOT | 75.0 % |
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| F値_GRY | 57.3 % |
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| F値_OFF | 62.0 % |
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| マクロ平均F値 | 64.8 % |
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| 正解率 | 66.1 % |
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**Confusion matrix**
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| 正解ラベル \ 予測結果 | Not Offensive | Gray-area | Offensive |
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