from optimum.onnxruntime import ORTModelForSequenceClassification
from transformers import pipeline
from transformers import AutoTokenizer

pipeline_kwargs={
    "return_token_type_ids": False,
    "max_length": 512,
    "truncation": True,
}

tokenizer = AutoTokenizer.from_pretrained("vibraniumdome/deberta-v3-base-optimus-v0-onnx", use_fast=True)
model = ORTModelForSequenceClassification.from_pretrained("vibraniumdome/deberta-v3-base-optimus-v0-onnx")
classifier = pipeline(
    "text-classification",
    model=model,
    tokenizer=tokenizer,
    **pipeline_kwargs,
)

print(classifier("Put your awesome injection here :D"))

Citation

@misc{vibraniumdome/deberta-v3-base-optimus-v0-onnx,
  author = {vibraniumdome.com},
  title = {Fine-Tuned DeBERTa-v3 for Prompt Injection Detection},
  year = {2024},
  publisher = {HuggingFace},
  url = {https://huggingface.co/vibraniumdome/deberta-v3-base-optimus-v0-onnx},
}