Instructions to use textdetox/glot500-toxicity-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textdetox/glot500-toxicity-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textdetox/glot500-toxicity-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textdetox/glot500-toxicity-classifier") model = AutoModelForSequenceClassification.from_pretrained("textdetox/glot500-toxicity-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ade031f8fd273ed8fb574c580ff6c7898865d56329d2345b03e15147ad962828
- Size of remote file:
- 5.43 kB
- SHA256:
- c5a8096f5086ff4c428c99c174f22862a763cd21294555cb6a9eca9e9d54dd0d
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