Instructions to use SummerSigh/Muti-Class-Redteaming with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SummerSigh/Muti-Class-Redteaming with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SummerSigh/Muti-Class-Redteaming")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SummerSigh/Muti-Class-Redteaming") model = AutoModelForSequenceClassification.from_pretrained("SummerSigh/Muti-Class-Redteaming", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from SummerSigh/Muti-Class-Redteaming: direct link, hf CLI and curl.
- Browser
- Download file 567 MB
-
https://huggingface.co/SummerSigh/Muti-Class-Redteaming/resolve/main/optimizer.pt
- Command line
-
hf download hf://SummerSigh/Muti-Class-Redteaming/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/SummerSigh/Muti-Class-Redteaming/resolve/main/optimizer.pt
567 MB
- Xet hash:
- dff81b9808afd951ec8e5533269f678fd95ff0dde92c63ea79f52c5db7a093fe
- Size of remote file:
- 567 MB
- SHA256:
- 77773ad0530b499711769b2d5fc366b92b4cac09c54e4b6830ab82b68f92945f
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