Instructions to use dima806/toxic-comments-classifier-distilbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dima806/toxic-comments-classifier-distilbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dima806/toxic-comments-classifier-distilbert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dima806/toxic-comments-classifier-distilbert") model = AutoModelForSequenceClassification.from_pretrained("dima806/toxic-comments-classifier-distilbert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 80bc262a0d7ea6e5b299e432e62e2c991302b87bb69b08461661e01da7c66d5f
- Size of remote file:
- 438 MB
- SHA256:
- 96e508c7528ae86c1b6c5ac35cae662ccc27aa15612caf811b59d4c6e3d090c4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.