Instructions to use s-nlp/roberta_first_toxicity_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use s-nlp/roberta_first_toxicity_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="s-nlp/roberta_first_toxicity_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("s-nlp/roberta_first_toxicity_classifier") model = AutoModelForSequenceClassification.from_pretrained("s-nlp/roberta_first_toxicity_classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 76bb38b1a2ea11f843df6b894bc8ee82bf61a54f52a9bd48f4bf853380d1c81d
- Size of remote file:
- 501 MB
- SHA256:
- beaca79ac1f1138be788b6de89ce4da4d435bc213dbb53487b83ce5f34ab82c7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.