openetruscan-classifier / v2 /metadata.json
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{
"version": "2.0.0",
"baseline_milestone": "8,091_verified",
"models": {
"classifier_legacy_cnn": {
"file": "classifier_legacy_cnn.onnx",
"type": "character_cnn",
"input_shape": [1, 128],
"labels": ["boundary", "commercial", "dedicatory", "funerary", "legal", "ownership", "votive"],
"portable": true,
"requires_embeddings": false
},
"classifier_legacy_transformer": {
"file": "classifier_legacy_transformer.onnx",
"type": "micro_transformer",
"input_shape": [1, 128],
"labels": ["boundary", "commercial", "dedicatory", "funerary", "legal", "ownership", "votive"],
"portable": true,
"requires_embeddings": false
},
"classifier_sota_mlp": {
"file": "classifier_sota_mlp.onnx",
"type": "embedding_mlp",
"input_shape": [1, 3072],
"labels": ["boundary", "commercial", "dedicatory", "funerary", "legal", "ownership", "votive"],
"portable": false,
"requires_embeddings": true,
"embedding_model": "text-embedding-004"
}
},
"deployment_notes": "For 99% accuracy (SOTA), the frontend must fetch 3072-dim embeddings from the /api/embed endpoint before calling the MLP. For zero-latency offline use, use the CNN."
}