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
- Xet hash:
- 1d451ee400e7d945dffe616270f52decf2c89bed8b6d7df4446a68b8eba324af
- Size of remote file:
- 712 MB
- SHA256:
- 0e20b1aabdc4c538964d321efc2209a01425e3adefee3348f138f14463d98cdb
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