Instructions to use textdetox/twitter-xlmr-toxicity-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textdetox/twitter-xlmr-toxicity-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textdetox/twitter-xlmr-toxicity-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textdetox/twitter-xlmr-toxicity-classifier") model = AutoModelForSequenceClassification.from_pretrained("textdetox/twitter-xlmr-toxicity-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 759e2a49c9200799a24be3501479878c1a1a4f61ed393c58a65fb41fcdc79605
- Size of remote file:
- 5.37 kB
- SHA256:
- 7e9045e261f431f3e8a4fe87aecf5eb7bb75f2822ded05da045c9997972441de
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