Instructions to use richterleo/toxicity_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use richterleo/toxicity_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="richterleo/toxicity_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("richterleo/toxicity_classifier") model = AutoModelForSequenceClassification.from_pretrained("richterleo/toxicity_classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ef32423cf4ba0cf3baa9f50e8bd866420ab3d42d873bb616597159dd977a7665
- Size of remote file:
- 4.6 kB
- SHA256:
- 177749ac98bcbf9bf1e8c89763a264362c7cf359ffb9d29135662e5a7436ab99
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.