Instructions to use mskov/distilbert-base-toxicity with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mskov/distilbert-base-toxicity with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mskov/distilbert-base-toxicity")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mskov/distilbert-base-toxicity") model = AutoModelForSequenceClassification.from_pretrained("mskov/distilbert-base-toxicity", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e8ec6c8ac7f6738e48dfd86e109092da7c1fc8d494db896af31fb40310f8fc44
- Size of remote file:
- 536 MB
- SHA256:
- 0d0b399daf293df8cf5bd15d9a0e45441f11e16010c82c0f747d1ffb4c5f237f
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