Text Classification
Transformers
PyTorch
Safetensors
Azerbaijani
deberta-v2
toxicity
azerbaijani
multi-label-classification
text-embeddings-inference
Instructions to use LocalDoc/azerbaijani_toxicity_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LocalDoc/azerbaijani_toxicity_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LocalDoc/azerbaijani_toxicity_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LocalDoc/azerbaijani_toxicity_classifier") model = AutoModelForSequenceClassification.from_pretrained("LocalDoc/azerbaijani_toxicity_classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 994dbaac4eaaaf1033ce39ecedd612e77b89dbfe8efd8de25ca24bea40caf6bc
- Size of remote file:
- 1.33 GB
- SHA256:
- 6f89419baf0f1aaad5cab7d53901e36a8c1af8f6b4ab58b15db9af32df656ead
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