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:
- 11ac8793a0b6ff78ad732a6756429942200627ea50d1bb804f332fb2bb2d9ac0
- Size of remote file:
- 4.09 kB
- SHA256:
- ec77fed025c2c515a5528b3f4e7a9f16ce7a0b0734f612bd4e463878108f7392
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