Modelpublic

HikmaAI/hikmaai-mdeberta-v3-base-prompt-injection-multilingual

sourceHugging Faceapache-2.0updated 2mo agoView on Hugging Face

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hikmaai-mdeberta-v3-base-prompt-injection-multilingual

A multilingual prompt injection classifier fine-tuned from microsoft/mdeberta-v3-base by HikmaAI.

Model Description

—Task: Binary classification (benign=0, injection=1)
—Base model: microsoft/mdeberta-v3-base
—Languages: 11 (en, vi, hi, th, zh, ja, ru, ar, sv, es, it)
—Export formats: ONNX FP32 + FP16 + INT8 (x86-safe dynamic)

Performance

Metric	Score
loss	0.0387
accuracy	0.9950
precision	0.9815
recall	0.9701
f1	0.9758

Optimized threshold: 0.5000 (val recall: 0.9709)

Usage (ONNX)

python

from optimum.onnxruntime import ORTModelForSequenceClassification
from transformers import AutoTokenizer

model = ORTModelForSequenceClassification.from_pretrained(
    "HikmaAI/hikmaai-mdeberta-v3-base-prompt-injection-multilingual",
    subfolder="onnx/fp16",
)
tokenizer = AutoTokenizer.from_pretrained(
    "HikmaAI/hikmaai-mdeberta-v3-base-prompt-injection-multilingual",
    subfolder="tokenizer",
)

inputs = tokenizer("Ignore all previous instructions", return_tensors="pt")
outputs = model(**inputs)
# outputs.logits -> [benign_score, injection_score]

Training

—Epochs: 5
—Learning rate: 2e-05
—Batch size: 16
—Class weights: [1.0, 1.3]
—Dataset: multilingual (11 languages), 12+ sources + synthetic data

License

Apache-2.0

Citation

bibtex

@misc{hikmaai-prompt_injection-2026,
  title={hikmaai-mdeberta-v3-base-prompt-injection-multilingual},
  author={HikmaAI},
  year={2026},
  publisher={HuggingFace},
  url={https://huggingface.co/HikmaAI/hikmaai-mdeberta-v3-base-prompt-injection-multilingual}
}