Instructions to use unitary/toxic-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use unitary/toxic-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="unitary/toxic-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("unitary/toxic-bert") model = AutoModelForSequenceClassification.from_pretrained("unitary/toxic-bert") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e1c8e5b7f52ad974dd275eba455e9005aa1e342bcb3d8c59106ffcae8a509d7b
- Size of remote file:
- 438 MB
- SHA256:
- cb47d3d2b3188c8518c455c19664c8fc7776e0aa4416bc89c58463fb0bd246a3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.