Model card
astris-embeddings-v1
Multilingual transformer sentence embeddings (intfloat e5) with an offline character-n-gram hashing fallback when the transformer is unavailable. L2-normalized vectors power semantic skill/title matching and approximate-nearest-neighbor candidate recall.
At a glance
| Kind | embedding |
| Version | 1.0.0 |
| Status | Active — contributing to scores |
| Ensemble weight | 0 |
| Trained at | Not trained yet |
| Trained on | n/a |
| Artifact | No artifact (heuristic or pre-training) |
Metrics
{
"backend": "e5_transformer",
"fallback": "char_ngram_hash",
"validation": "synthetic_seed",
"real_cohort": "pending",
"normalization": "l2"
}Notes
Capability layer, not a retention voter — weight 0. Degrades to the hashing fallback offline; see api/ml/embeddings.py.