Instructions to use rudycaz/promptguard2-promptinj-adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use rudycaz/promptguard2-promptinj-adapter with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("meta-llama/Llama-Prompt-Guard-2-86M") model = PeftModel.from_pretrained(base_model, "rudycaz/promptguard2-promptinj-adapter") - Transformers
How to use rudycaz/promptguard2-promptinj-adapter with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("rudycaz/promptguard2-promptinj-adapter", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 133 Bytes
2c5beb9 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:1c6dfa928f8b49449a6b0d8751d97e0149b48f5ecef26b0ff877d1eeccd3712f
size 16335938
|