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")# pip install -U transformers accelerate # 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
Download optimizer.pt from textdetox/glot500-toxicity-classifier: direct link, hf CLI and curl.
- Browser
- Download file 3.15 GB
-
https://huggingface.co/textdetox/glot500-toxicity-classifier/resolve/main/optimizer.pt
- Command line
-
hf download hf://textdetox/glot500-toxicity-classifier/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/textdetox/glot500-toxicity-classifier/resolve/main/optimizer.pt
3.15 GB
- Xet hash:
- b74100d04c9dde3d1fdf0487fba42f63acf83528129336676544aaa45d9046c2
- Size of remote file:
- 3.15 GB
- SHA256:
- a2ce7d0b94d1a81a8c50314e5d1ba140edf802924411ec99f7bbe285f1be0d75
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