| --- |
| license: apache-2.0 |
| library_name: numpy |
| tags: |
| - governed-ai |
| - khipu |
| - szl-holdings |
| - embedding |
| - silhouette |
| - software |
| - reference |
| - test-fixture |
| --- |
| |
| > **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](https://github.com/szl-holdings/szl-khipu) |
| Sibling card: [SZLHOLDINGS/szl-khipu](https://huggingface.co/SZLHOLDINGS/szl-khipu) |
| The larger statistical MiniEmbed (3290 × 128) lives on [SZLHOLDINGS/szl-kernels](https://huggingface.co/SZLHOLDINGS/szl-kernels) — a different artifact. Do not mix them. |
|
|
| ```python |
| 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). |
|
|
| ## Bench (this tree) |
|
|
| `TRAINING_RECEIPT.json` seed `20260721` · honesty **REPORTED** |
|
|
| | Metric | Value | |
| |---|---| |
| | V×d | 64 × 12 | |
| | method | hash+table L2 | |
| | weights | `mini_embed.npz` sha256 `ae31a3a7214d1f142d8ea3f4f86c35bdedd7c108bc5d04ea00c87e7b674e6e3b` | |
|
|
| Infers on `POST /api/infer {"kind":"mini_embed","token":"F18"}`. **Not neural. Not 3290×128.** |
|
|
| ## What it is NOT |
|
|
| - **Not** the [SZLHOLDINGS/szl-kernels](https://huggingface.co/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](https://orcid.org/0009-0001-0110-4173). |
|
|
| ## Artifact evidence |
|
|
| `mini_embed.npz` is present (6,892 bytes). SHA-256: |
|
|
| `ae31a3a7214d1f142d8ea3f4f86c35bdedd7c108bc5d04ea00c87e7b674e6e3b` |
|
|
| The archive hash matches `TRAINING_RECEIPT.json`. Its arrays were inspected |
| with `numpy.load(..., allow_pickle=False)`; numeric values were finite. |
|
|
| | Array | Shape | Data type | |
| | --- | --- | --- | |
| | `table` | `[64, 12]` | `float64` | |
| | `V` | `[]` | `int64` | |
| | `D` | `[]` | `int64` | |
|
|
| A matching unsigned receipt establishes local artifact consistency. Training |
| metrics remain reported synthetic results; this check does not independently |
| reproduce training or establish deployment, general intelligence, or production readiness. |
|
|
