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:
- e844e7c639f4b249ece322a03805806ff510bbae42d37f9cbfcdff81b029da07
- Size of remote file:
- 627 Bytes
- SHA256:
- e469fc024db82e94f79bec728ae3376a2df567f59d3e7a7fc3daad420213a69c
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