A paired non-inferiority test against the pristine model at n=2800 found a real capability loss on:
arithmetic: pristine 0.351 → this model 0.269 (bound on the drop +0.099, exceeds the 3% margin)
It is published for transparency and for uses where the affected axis
does not matter. Do not treat it as capability-preserving.
📄 Read the 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 SmolLM2-1.7B-Instruct
0.427
0.360
Ektomē (this model)
0.430
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
arithmetic
1400
0.351
0.269
+0.099
FAIL
instruction
600
0.415
0.442
-0.008
PASS
knowledge
400
0.542
0.522
+0.050
INCONCLUSIVE
reasoning
400
0.305
0.268
+0.068
INCONCLUSIVE
Overall: FAIL (3% margin, n=2800, alpha=0.05)
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
0.0
15
instr_pass
0.8
1.0
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
file
bits
notes
Ektome-SmolLM2-1.7Bi-Q8_0.gguf
8
near-lossless
Ektome-SmolLM2-1.7Bi-Q6_K.gguf
6
Ektome-SmolLM2-1.7Bi-Q5_K_M.gguf
5
Ektome-SmolLM2-1.7Bi-Q4_K_M.gguf
4
imatrix
Ektome-SmolLM2-1.7Bi-IQ4_XS.gguf
4
imatrix, smallest usable
Ektome-SmolLM2-1.7Bi-IQ3_M.gguf
3
imatrix
IQ* variants are imatrix-quantised — better quality per bit at low precision.
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
1@software{ektome_Ektome-SmolLM2-1.7Bi-PristinelyUncensored,
2 title = {Ektome-SmolLM2-1.7Bi-PristinelyUncensored},
3 author = {Zynerji},
4 year = {2026},
5 url = {https://huggingface.co/Zynerji/Ektome-SmolLM2-1.7Bi-PristinelyUncensored}
6}
