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:
- 869fc2a5567398b8d3333f3462c98a9bd297aa29b1bae7fff935f28351718cae
- Size of remote file:
- 536 MB
- SHA256:
- 07e8990aac3cc8135bcc91a841c2606eeb269e6c79d0a00bbd39ed5579b93340
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