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")# pip install -U transformers accelerate # 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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (0222010dd43b41821fcc933fe186da78a5e90372) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>92d6598
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