Mitra (Tab2D) inference engine — zero-shot forward pass only (no fine-tuning; see the crate
README for why). Architecture: per-feature quantile-bucketize embedding → prepend a learned
y-embedding as an extra “feature” column → 12 layers of (row self/cross-attention → MLP →
feature self-attention → MLP) → final LayerNorm + linear head, read out at the y-column.