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 pytorch_model.bin from SummerSigh/Muti-Class-Redteaming: direct link, hf CLI and curl.
- Browser
- Download file 283 MB
-
https://huggingface.co/SummerSigh/Muti-Class-Redteaming/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SummerSigh/Muti-Class-Redteaming/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SummerSigh/Muti-Class-Redteaming/resolve/main/pytorch_model.bin
283 MB
- Xet hash:
- 7ddae431bd8474e0b18a8edeab58ac46bbf5979150af7210803373ef9a06c916
- Size of remote file:
- 283 MB
- SHA256:
- d36e58a1c568f2c1e6ac4699a2a7d4cc00cd34cebffecd702f5ee189daeb2c69
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