Instructions to use jpcorb20/toxic-detector-distilroberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jpcorb20/toxic-detector-distilroberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jpcorb20/toxic-detector-distilroberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jpcorb20/toxic-detector-distilroberta") model = AutoModelForSequenceClassification.from_pretrained("jpcorb20/toxic-detector-distilroberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a126f2d03db96785e0eeea3222cea5e392863db27a6e617821748f6004bfb6bb
- Size of remote file:
- 331 MB
- SHA256:
- deda16f5c83af8b08fb906222c341d5629762c65282897b80316265ec0959656
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.