Any significant changes to the benchmark evaluation code, benchmark output, benchmark results table, or the underlying dataset will be noted here.
- Merged
public_prompt_injectionandinternal_prompt_injectioncategories into a singleprompt_injection
- Added updated results for
Epivolis/Hyperionto the benchmark results table due to error in previous results due to incorrectinjection_labelvalue
- Added updated results for
Lakera Guardto the benchmark results table
- Added Azure AI Prompt Shields to the benchmark results table
- Updated
protectai/deberta-v3-base-prompt-injectionresults to account for slight increase in score afterstridewas added to chunking code
- Added the date the benchmark was run to the benchmark output
- Added
strideparameter of 25% of the model'smax_lengthto theHuggingFaceModelEvaluationimplementation of tokenizing and chunking long text for classification
Note: Any model's scores affected by this change were updated in the benchmark results table.
- Added results for Lakera Guard to the benchmark results table
- Added results for
protectai/deberta-v3-base-prompt-injectionto the benchmark results table - Added results for
WhyLabs LangKitto the benchmark results table - Added results for
fmops/distilbert-prompt-injectionto the benchmark results table - Added results for
deepset/deberta-v3-base-injectionto the benchmark results table - Added results for
Myadav/setfit-prompt-injection-MiniLM-L3-v2to the benchmark results table - Added results for
Epivolis/Hyperionto the benchmark results table
- Added
HuggingFaceModelEvaluationclass for conveniently evaluating Hugging Face models