Instructions to use unitary/unbiased-toxic-roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use unitary/unbiased-toxic-roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="unitary/unbiased-toxic-roberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("unitary/unbiased-toxic-roberta") model = AutoModelForSequenceClassification.from_pretrained("unitary/unbiased-toxic-roberta", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 809c7781e04a1f5d619641a6abbaf0d3eece2a64328f55d4450a17663b265b18
- Size of remote file:
- 499 MB
- SHA256:
- f1cfe8f98a22fff5cf77c150d76ea0328575995aa9b7eb0f566f624842379ba5
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