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README.md

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+---
+language:
+  - en
+tags:
+  - deckergui
+  - token-classification
+  - entity-recognition
+  - ecosystem
+  - gate-prediction
+license: mit
+pipeline_tag: token-classification
+---
+
+# DGUI-GatePredictor
+
+Token classification model for predicting DGM gate outcomes in the DeckerGUI ecosystem.
+
+## Model Details
+
+- **Model Type:** Token Classification (Sequence Labeling)
+- **Training Data:** deckergui-seed-status-events, deckergui-agent-coordination
+- **Architecture:** DistilBERT-base with custom classification head
+- **Labels:** gate_pass, gate_block, quota_exceeded, key_revoked, scope_violation
+- **DeckerGUI Version:** v2.0.0
+
+## Usage
+
+```python
+from transformers import pipeline
+
+classifier = pipeline("token-classification", model="ctaxnagomi/DGUI-GatePredictor")
+
+result = classifier("Agent dgui-emitter requested context.bundle with key 0xb553de32")
+print(result)
+```
+
+## Training
+
+Trained on synthetic DeckerGUI ecosystem data:
+- 120 seed status events
+- 180 agent coordination records
+- Gate decision patterns from CaaS federation
+
+## Citation
+
+```bibtex
+@software{deckergui_gate_predictor_2026,
+  title={DGUI-GatePredictor: Token Classification for DGM Gate Outcomes},
+  author={Wan Mohd Azizi bin Wan Hosen},
+  year={2026},
+  url={https://huggingface.co/ctaxnagomi/DGUI-GatePredictor}
+}
+```