Text Classification
Transformers
PyTorch
TensorFlow
Safetensors
Russian
bert
toxic comments classification
Instructions to use s-nlp/russian_toxicity_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use s-nlp/russian_toxicity_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="s-nlp/russian_toxicity_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("s-nlp/russian_toxicity_classifier") model = AutoModelForSequenceClassification.from_pretrained("s-nlp/russian_toxicity_classifier") - Inference
- Notebooks
- Google Colab
- Kaggle
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## Citation
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```
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@article{dementieva2022russe,
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title={RUSSE-2022: Findings of the First Russian Detoxification Shared Task Based on Parallel Corpora},
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## Citation
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To acknowledge our work, please, use the corresponding citation:
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```
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@article{dementieva2022russe,
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title={RUSSE-2022: Findings of the First Russian Detoxification Shared Task Based on Parallel Corpora},
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