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perfecXion
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reacted to their post with 👍 3 days ago
# IntentGuard: Open-Source Vertical Intent Classifiers for LLM Guardrails Three models published to the Hub: - [perfecXion/intentguard-finance](https://huggingface.co/perfecXion/intentguard-finance) - [perfecXion/intentguard-healthcare](https://huggingface.co/perfecXion/intentguard-healthcare) - [perfecXion/intentguard-legal](https://huggingface.co/perfecXion/intentguard-legal) DeBERTa-v3-xsmall fine-tuned for three-way classification: **allow**, **deny**, or **abstain**. ONNX + INT8 quantized, under 80MB, p99 <30ms on CPU. Margin-based thresholds (not argmax) — uncertain queries route to clarification instead of forcing a guess. **Eval results (adversarial test sets, ~470-480 examples per vertical):** | Vertical | Accuracy | Legit-Block Rate | Off-Topic-Pass Rate | |----------|----------|------------------|---------------------| | Finance | 99.6% | 0.00% | 0.00% | | Healthcare | 98.9% | 0.00% | 0.98% | | Legal | 97.9% | 0.00% | 0.50% | ```bash docker run -p 8080:8080 ghcr.io/perfecxion/intentguard:finance-latest curl -X POST http://localhost:8080/v1/classify \ -H "Content-Type: application/json" \ -d '{"messages": [{"role": "user", "content": "What are current mortgage rates?"}]}' ``` Apache 2.0. Full pipeline + Docker configs on [GitHub](https://github.com/perfecxion-ai/intentguard). Feedback welcome on domain coverage, adversarial robustness, and multilingual demand.
posted an update 4 days ago
# IntentGuard: Open-Source Vertical Intent Classifiers for LLM Guardrails Three models published to the Hub: - [perfecXion/intentguard-finance](https://huggingface.co/perfecXion/intentguard-finance) - [perfecXion/intentguard-healthcare](https://huggingface.co/perfecXion/intentguard-healthcare) - [perfecXion/intentguard-legal](https://huggingface.co/perfecXion/intentguard-legal) DeBERTa-v3-xsmall fine-tuned for three-way classification: **allow**, **deny**, or **abstain**. ONNX + INT8 quantized, under 80MB, p99 <30ms on CPU. Margin-based thresholds (not argmax) — uncertain queries route to clarification instead of forcing a guess. **Eval results (adversarial test sets, ~470-480 examples per vertical):** | Vertical | Accuracy | Legit-Block Rate | Off-Topic-Pass Rate | |----------|----------|------------------|---------------------| | Finance | 99.6% | 0.00% | 0.00% | | Healthcare | 98.9% | 0.00% | 0.98% | | Legal | 97.9% | 0.00% | 0.50% | ```bash docker run -p 8080:8080 ghcr.io/perfecxion/intentguard:finance-latest curl -X POST http://localhost:8080/v1/classify \ -H "Content-Type: application/json" \ -d '{"messages": [{"role": "user", "content": "What are current mortgage rates?"}]}' ``` Apache 2.0. Full pipeline + Docker configs on [GitHub](https://github.com/perfecxion-ai/intentguard). Feedback welcome on domain coverage, adversarial robustness, and multilingual demand.
updated a model 6 days ago
perfecXion/intentguard-legal
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