Instructions to use mskov/distilbert-base-toxicity with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mskov/distilbert-base-toxicity with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mskov/distilbert-base-toxicity")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mskov/distilbert-base-toxicity") model = AutoModelForSequenceClassification.from_pretrained("mskov/distilbert-base-toxicity", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from mskov/distilbert-base-toxicity: direct link, hf CLI and curl.
- Browser
- Download file 536 MB
-
https://huggingface.co/mskov/distilbert-base-toxicity/resolve/refs%2Fpr%2F1/optimizer.pt
- Command line
-
hf download hf://mskov/distilbert-base-toxicity@refs/pr/1/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/mskov/distilbert-base-toxicity/resolve/refs%2Fpr%2F1/optimizer.pt
536 MB
- Xet hash:
- e8ec6c8ac7f6738e48dfd86e109092da7c1fc8d494db896af31fb40310f8fc44
- Size of remote file:
- 536 MB
- SHA256:
- 0d0b399daf293df8cf5bd15d9a0e45441f11e16010c82c0f747d1ffb4c5f237f
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