Text Classification
Transformers
PyTorch
English
distilbert
toxic text classification
text-embeddings-inference
Instructions to use tensor-trek/distilbert-toxicity-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tensor-trek/distilbert-toxicity-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tensor-trek/distilbert-toxicity-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tensor-trek/distilbert-toxicity-classifier") model = AutoModelForSequenceClassification.from_pretrained("tensor-trek/distilbert-toxicity-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a67f40c4dc7755a8dc98b35dadf6ed5e4765a8547a3189a322cd185e24ff4daf
- Size of remote file:
- 268 MB
- SHA256:
- 0f48dd5c306389ede28fd86a49ff3ceb2d917d0027a564e8bd6c4b065781bb37
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