Text Classification
Laya
ONNX
GGUF
English
Hindi
system-one
calibrated-decisions
guardrails
prompt-injection
mcp
hinglish
edge-ai
owasp
Eval Results (legacy)
Instructions to use eulogik/suraksha-450m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Laya
How to use eulogik/suraksha-450m with Laya:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
SURAKSHA 450M is out: calibrated guard for prompts + MCP tool calls
#1
by GautamKishore - opened
450M open-weight guard by Eulogik. One forward pass gives calibrated P(prompt-injection), P(jailbreak), P(PII-leak), P(tool-risk), in English + Hinglish + Hindi. Apache-2.0, trained on a Mac mini M4 for $0.
Measured on frozen heldout n=3058: injection 0.98, tool-risk 1.0, severity 0.98, worst fitted ECE 0.022. ONNX 37/37 parity.
Code: https://github.com/eulogik/suraksha
Dataset: https://huggingface.co/datasets/eulogik/suraksha-guard-38k
Feedback welcome, especially Hinglish red-team cases.