MiniEmbed-Nano
A deterministic 64 × 12 NumPy table for inspecting hash-based token vectors and simple pooling.
Artifact: NumPy embedding table · Stage: Software / reference / test fixture
Command Lab · Canonical source · Reviewed evidence
Before you use it
- This is a small reference table, not a trained neural embedding model or the separate 3290 × 128 SVD MiniEmbed artifact.
- The example constructs a new table; it does not verify loading or reproducing the published archive.
- No retrieval or analogy score is established for this artifact. Bind its exact revision, array schema, and loader before comparison.
Status: SOFTWARE / REFERENCE / TEST FIXTURE. Not a production model.
This Hub repository contains a bare NumPy archive. The loading and forward-pass
implementation lives in the canonical szl_khipu package; no packaged Hub
loader or config.json is shipped alongside these weights. Treat this as a
software fixture until its complete inference contract is independently verified.
MiniEmbed-Nano
Tiny hash+table embed: V=64, d=12, L2-normalized rows. Not a foundation embed. Not neural. Not MiniEmbed 3290×128.
Canonical source: szl-holdings/szl-khipu
Sibling card: SZLHOLDINGS/szl-khipu
The larger statistical MiniEmbed (3290 × 128) lives on SZLHOLDINGS/szl-kernels — a different artifact. Do not mix them.
Construction example for the canonical package: this builds and saves a
new deterministic 64 × 12 table. It does not load or independently verify the
published mini_embed.npz.
from szl_khipu.train import mini_embed
emb = mini_embed.build(seed=20260721)
vec = emb.embed("knot the run")
print(emb.V, emb.D, vec.shape)
# 64 12 (12,)
emb.save_npz("mini_embed.npz")
What it does
- SHA-256 token id modulo 64. Mean-pool then L2. Deterministic given seed.
- Built here on CPU NumPy. Honesty REPORTED. Energy UNAVAILABLE.
- No analogy score. No retrieval score. No SVD variance claim (that belongs to the 3290×128 table).
Reported synthetic fixture evidence
TRAINING_RECEIPT.json seed 20260721 · honesty REPORTED
| Metric | Value |
|---|---|
| V×d | 64 × 12 |
| method | hash+table L2 |
| weights | mini_embed.npz receipt-reported sha256 ae31a3a7214d1f142d8ea3f4f86c35bdedd7c108bc5d04ea00c87e7b674e6e3b |
The related demo documents an application-specific POST /api/infer route.
This archive repository establishes no hosted endpoint, served revision, or
deployment guarantee. The route is illustrative application context.
What it is NOT
- Not the SZLHOLDINGS/szl-kernels MiniEmbed (3290 × 128, SVD var 0.3146).
- Not neural. Not word2vec. Not a foundation embed.
- Not 1.5B. Not Qwen.
- Not proven trust. Λ uniqueness remains Conjecture 1 OPEN.
- Energy UNAVAILABLE. CUDA UNAVAILABLE. Never a fabricated joule.
Honesty
| Claim | Label | What-NOT |
|---|---|---|
| Table built in this package | REPORTED | V=64 d=12, not 3290×128 |
| Neural / trained embed | FALSE | hash+table, not SGD |
| Analogy / retrieval score | UNAVAILABLE | not measured |
| Energy | UNAVAILABLE | never a fabricated joule |
| CUDA | UNAVAILABLE | CPU numpy LIVE |
Doctrine v11 LOCKED · 749/14/163 · locked-proven 8. Apache-2.0. Copyright 2026 SZL Holdings · Stephen P. Lutar Jr. · ORCID 0009-0001-0110-4173.
Artifact evidence
The previous card reports mini_embed.npz (6,892 bytes). Receipt-reported SHA-256 (not rehashed in this review):
ae31a3a7214d1f142d8ea3f4f86c35bdedd7c108bc5d04ea00c87e7b674e6e3b
The previous card reported that the archive matched the unsigned training
receipt and that numpy.load(..., allow_pickle=False) found finite numeric
arrays. The table below preserves that historical report. The September 30,
2026 card review read pinned text and the receipt; it did not download, rehash,
or inspect the archive, and did not replay training.
| Array | Shape | Data type |
|---|---|---|
table |
[64, 12] |
float64 |
V |
[] |
int64 |
D |
[] |
int64 |
The retained receipt labels these reported synthetic fixture results REPORTED.
An independently checked archive/receipt match could establish local artifact consistency; an unsigned digest would still not authenticate authorship or measurement. These preserved receipt and array reports establish no new training replay, independent evaluation, deployment, or production readiness.
Reviewed Hub text: immutable snapshot 01e82f36ff722528233f76daf899c18f8cb5aaa2.
Reviewed publisher source: hf/MiniEmbed-Nano/README.md at e53e3d24b22e356eb986c373aee27b3b3e7947ec.
The shared unsigned TRAINING_RECEIPT.json, timestamped
2026-08-29T17:11:32.518042+00:00, enumerates four artifacts. Only its
artifacts["mini_embed.npz"] entry describes this archive; the other
entries do not establish that sibling artifacts are present in this repository.
The receipt does not bind its training run to the reviewed source commit.
SZL Orbit artwork: source · CC BY 4.0. Software and artifact licensing remain declared above.