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 model.safetensors from textdetox/glot500-toxicity-classifier: direct link, hf CLI and curl.
- Browser
- Download file 1.58 GB
-
https://huggingface.co/textdetox/glot500-toxicity-classifier/resolve/main/model.safetensors
- Command line
-
hf download hf://textdetox/glot500-toxicity-classifier/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/textdetox/glot500-toxicity-classifier/resolve/main/model.safetensors
1.58 GB
- Xet hash:
- 2a2342161c97ed9f151aad986316a72b2e46c53d587b8bd516e9867bcfb50f39
- Size of remote file:
- 1.58 GB
- SHA256:
- ba6b2427495d895d7170c4169fb7e2077ba47a848503fca1096732079a094dd2
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