Instructions to use fasherr/toxicity_rubert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fasherr/toxicity_rubert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fasherr/toxicity_rubert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fasherr/toxicity_rubert") model = AutoModelForSequenceClassification.from_pretrained("fasherr/toxicity_rubert") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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tags:
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- toxicity
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widget:
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- text: "Т
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---
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Тун тун
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tags:
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- toxicity
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widget:
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- text: "Ты сегодня прекрасно выглядишь!"
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example_title: "NEUTRAL - 99.29%"
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- text: "Ты очень плохой человек"
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example_title: "TOXIC - 99.98%"
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- text: "Сегодня ясная погода"
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example_title: "NEUTRAL - 100.00%"
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---
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Тун тун
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