Instructions to use CodeHima/TOSBertV2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CodeHima/TOSBertV2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CodeHima/TOSBertV2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CodeHima/TOSBertV2") model = AutoModelForSequenceClassification.from_pretrained("CodeHima/TOSBertV2") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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The model performs multi-class classification on individual sentences or clauses, categorizing them into three levels of unfairness:
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### Training Data
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The model performs multi-class classification on individual sentences or clauses, categorizing them into three levels of unfairness:
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0. Clearly Fair
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1. Potentially Unfair
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2. Clearly Unfair
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### Training Data
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