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:
- 8cfc86e6fbc5c99245477a5488d4fea90489ef9c85eb3a21773ebcce1c0c9676
- Size of remote file:
- 14.2 kB
- SHA256:
- dfab2159eb0b6344df83e2bb46d275278ad9543310df806da1edad33317ae9ff
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