Instructions to use textdetox/xlmr-base-toxicity-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textdetox/xlmr-base-toxicity-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textdetox/xlmr-base-toxicity-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textdetox/xlmr-base-toxicity-classifier") model = AutoModelForSequenceClassification.from_pretrained("textdetox/xlmr-base-toxicity-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from textdetox/xlmr-base-toxicity-classifier: direct link, hf CLI and curl.
- Browser
- Download file 4.66 kB
-
https://huggingface.co/textdetox/xlmr-base-toxicity-classifier/resolve/main/training_args.bin
- Command line
-
hf download hf://textdetox/xlmr-base-toxicity-classifier/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/textdetox/xlmr-base-toxicity-classifier/resolve/main/training_args.bin
4.66 kB
- Xet hash:
- b7e8eee0776eb451e59d3dcbf4bd27620f6c1d1e60630bd2f155207a1e7852a0
- Size of remote file:
- 4.66 kB
- SHA256:
- 5e5669b8832cbf5841d48301e9864d3640c85cceb7efe18e9227169755b90d11
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.