Hugging Face's logo

KIMMISEON
/
distilbert-prompt-guard-4class

Text Classification
Transformers
Safetensors
English
distilbert
prompt-injection-detection
jailbreak-detection
security
text-embeddings-inference
Model card Files
xet
 Community
How to use from the
Use from the
Transformers library
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-classification", model="KIMMISEON/distilbert-prompt-guard-4class")
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("KIMMISEON/distilbert-prompt-guard-4class")
model = AutoModelForSequenceClassification.from_pretrained("KIMMISEON/distilbert-prompt-guard-4class", device_map="auto")
Quick Links

distilbert-prompt-guard-4class

This is a 4-class DistilBERT classifier fine-tuned for:

  • benign
  • prompt_injection
  • jailbreak
  • sensitive_access

Base model: {BASE_MODEL}

Datasets used:

  • dmilush/shieldlm-prompt-injection
  • antijection/prompt-injection-dataset-v1
  • leolee99/NotInject

Notes:

  • sensitive_access is a custom merged class created from exfiltration / prompt-extraction / excessive-agency style attacks.
  • Please review upstream dataset licenses before commercial use.
Downloads last month
13
Safetensors
Model size
67M params
Tensor type
F32
·
Inference Providers NEW
Text Classification
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for KIMMISEON/distilbert-prompt-guard-4class

Base model

distilbert/distilbert-base-uncased
Finetuned
(12199)
this model

Datasets used to train KIMMISEON/distilbert-prompt-guard-4class