Instructions to use codesagar/prompt-guard-classification-v12 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codesagar/prompt-guard-classification-v12 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("codesagar/prompt-guard-classification-v12", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download adapter_model.safetensors from codesagar/prompt-guard-classification-v12: direct link, hf CLI and curl.
- Browser
- Download file 168 MB
-
https://huggingface.co/codesagar/prompt-guard-classification-v12/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://codesagar/prompt-guard-classification-v12/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/codesagar/prompt-guard-classification-v12/resolve/main/adapter_model.safetensors
168 MB
- Xet hash:
- 9538a817b55a3bee088df354a3ab56ecbaa11d66ce43ff326c25f9f5caadecac
- Size of remote file:
- 168 MB
- SHA256:
- a2a7b335e40f2bf267399a7da32237d78d05c22da7628aaf7ee0312bf40c0390
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