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Model: Zynerji/Ektome-Qwen1.5-0.5B-Chat-PristinelyUncensored
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---
license: apache-2.0
base_model: Qwen/Qwen1.5-0.5B-Chat
tags:
- uncensored
- abliterated
- uncertified
- ektome
- sphragis
- qwen1.5
language:
- en
pipeline_tag: text-generation
---
![Ektome-Qwen1.5-0.5B-Chat-PristinelyUncensored](./hero.png)
# Ektome-Qwen1.5-0.5B-Chat-PristinelyUncensored
**Uncensored. No n=2800 certificate has been run for this model, so no capability-retention claim is made.**
> **compliance 0.06 to 1.00 at capability -0.007 vs pristine.**
$$\colorbox{black}{$\color{white}
\begin{array}{ll}
\textsf{EKTOME CERTIFICATE} & {} \\
\textsf{capability} & \textsf{NOT} \\
\textsf{margin} & 3\% \\
\textsf{items } n & 200 \\
\textsf{worst-axis bound} & -0.008 \\
\textsf{compliance} & 0.06 \rightarrow 1.00 \\
\end{array}$}$$
> ### ⚠️ Not certified
>
> No n=2800 paired certificate exists for this model. Any numbers below are
> point estimates with no confidence interval.
📄 **[Read the whitepaper (PDF)](./whitepaper.pdf)** — full method, receipts and certification.
The PDF is the authoritative document: dark-typeset, with the complete derivation, the
per-axis certificate and the reproducibility hashes.
---
## Why this exists
Standard abliteration removes a coarse *refusal direction* that is entangled with
directions carrying knowledge and reasoning. The result is an uncensored model with a
capability tax that is **almost never measured**.
Ektomē (ἐκτομή, *excision*) isolates and removes only the refusal-**specific**
component, leaving general helpfulness intact, and does so norm-preservingly on the
pristine model — no training, no distillation, no damage to repair. The extraction
depth is selected per model by automated search against measured compliance.
The estimator, excision operator and depth-selection procedure are proprietary.
What is published here is the **measured outcome** and the evidence for it, which you
can verify against the artifacts in this repo.
## The receipt
| model | capability (MMLU-val) ↑ | compliance on harmful ↑ |
|---|---|---|
| pristine `Qwen1.5-0.5B-Chat` | 0.328 | 0.060 |
| **Ektomē (this model)** | **0.335** | **1.000** |
These are **point estimates with no confidence interval** — which is precisely why the next section exists.
## The certificate
Capability retention is certified by a paired non-inferiority test against the pristine
model (exact McNemar, Holm-corrected, one-sided bootstrap bound on the drop $d$ vs a
3% margin):
| axis | n | ref | cand | d upper | verdict |
|---|---|---|---|---|---|
| MMLU-val (POINT ESTIMATE, n=200, no CI) | 200 | 0.328 | 0.335 | -0.008 | UNCERTIFIED |
**Overall: NOT CERTIFIED - no n=2800 paired test has been run for this model**
Reproducible from `seed=20260726`, pack `sha256:7bbaff877146e081…`.
### Generation health checks
| metric | pristine | Ektomē | n |
|---|---|---|---|
| `foreign_rate` | 0.0 | 0.0 | 15 |
| `degen_rate` | 0.0 | 0.1 | 15 |
| `instr_pass` | 1.0 | 0.8 | 5 |
These are **degeneration guards** — code-switching, babbling, format compliance —
not capability measures. Note the sample sizes: they detect a broken model, not a
subtly weaker one. The capability claim rests on the certificate above, not here.
## Quantisations
_No quantisations have been published for this model yet — bf16 weights only._
## Limitations
The certificate bounds **capability retention only**. It does not certify safety, factual
accuracy, or fitness for any purpose. Axes marked *inconclusive* are honestly
under-powered, and the certificate states the $n$ needed to resolve them. Compliance uses
a keyword classifier — a proxy that evasive phrasing can fool. **This model is uncensored
by construction: it will not refuse, and you are accountable for what you do with it.**
## Citation
```bibtex
@software{ektome_Ektome-Qwen1.5-0.5B-Chat-PristinelyUncensored,
title = {Ektome-Qwen1.5-0.5B-Chat-PristinelyUncensored},
author = {Zynerji},
year = {2026},
url = {https://huggingface.co/Zynerji/Ektome-Qwen1.5-0.5B-Chat-PristinelyUncensored}
}
```

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{
"sphragis_version": "0.1.0",
"generated_at": "2026-07-27T18:34:00.914337+00:00",
"reference": {
"endpoint": "http://127.0.0.1:8080/v1",
"model": "ref"
},
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"endpoint": "http://127.0.0.1:8081/v1",
"model": "cand"
},
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"claim": "At least one axis shows a statistically significant accuracy regression (exact McNemar, Holm-corrected, alpha=0.05).",
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"axis": "arithmetic",
"n": 1400,
"counts": {
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"reason": "significant_regression"
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"n": 600,
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{
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"n": 400,
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}
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"params": {
"margin": 0.03,
"alpha": 0.05,
"n_floor": 30,
"power": 0.8,
"n_boot": 4000,
"seed": 0
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{
"status": "SHIP",
"target": 0.99,
"SE_mmlu": 0.023465067121148406,
"base_compliance": 0.06,
"compliance": 1.0,
"base_cap": 0.3275,
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"base_model": "Qwen/Qwen1.5-0.5B-Chat",
"_note": "Redacted: search trajectory, selected depth and edit-scope removed. Reported values are the measured outcome only."
}

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