AutoCyberAI/crp-intent-setfit

CRP Intent / Speech-Act Classifier

A SetFit sentence-transformer classifier that maps a user turn into one of four CRP speech acts: request, question, assertion, or expressive. Trained on Banking77, SNIPS, and synthetic CRP-style templates. Used by crp.isa.intent to decide how a turn should be routed and framed in the positioned agent loop.

Model description

• Architecture: SetFit on sentence-transformers/all-MiniLM-L6-v2 (22M params).
• Labels: request, question, assertion, expressive.
• Held-out accuracy: 0.934 (2,000-example held-out slice from the training mix).
• Production prompt score: 18/20 correctly classified.
• Inference budget: ~10 ms on CPU; governed by crp.ml.registry.ModelManager.

Intended use

from setfit import SetFitModel
model = SetFitModel.from_pretrained('AutoCyberAI/crp-intent-setfit')
print(model.predict(['Please scan the repository for compliance issues.']))  # ['request']

Limitations

• The model is trained on English banking/intent datasets plus synthetic CRP templates; performance may degrade on code-heavy or non-English inputs.
• It is an advisory classifier — the rule-based fallback in crp.isa.intent remains the degraded path if the model is unavailable or the latency budget is exceeded.

Citation

@misc{crp-intent-setfit,
  title={{CRP Intent / Speech-Act Classifier}},
  author={{AutoCyber AI}},
  year={2026},
  howpublished={\url{https://huggingface.co/AutoCyberAI/crp-intent-setfit}}
}

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This model is part of the Context Relay Protocol (CRP) v6 Phase A managed-model suite. Learn more at https://crprotocol.io.