Instructions to use codesagar/prompt-guard-reasoning-v9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codesagar/prompt-guard-reasoning-v9 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("codesagar/prompt-guard-reasoning-v9", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download adapter_model.safetensors from codesagar/prompt-guard-reasoning-v9: direct link, hf CLI and curl.
- Browser
- Download file 168 MB
-
https://huggingface.co/codesagar/prompt-guard-reasoning-v9/resolve/2cce3445e5038e7dc52754cc263c4b20c2e9033a/adapter_model.safetensors
- Command line
-
hf download hf://codesagar/prompt-guard-reasoning-v9@2cce3445e5038e7dc52754cc263c4b20c2e9033a/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/codesagar/prompt-guard-reasoning-v9/resolve/2cce3445e5038e7dc52754cc263c4b20c2e9033a/adapter_model.safetensors
168 MB
- Xet hash:
- 94cf646103a74fcc10c938ce17d8125089c92900c7cbecfd3583a6d4393f05ea
- Size of remote file:
- 168 MB
- SHA256:
- ec4bf66f2b2dd9dfa774efad6f700c8bebe9ceb9ddb0b2cd012c279cad5c0659
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.