c03d4c4377
Model: Zynerji/Ektome-Qwen2.5-Coder-7B-Instruct-PristinelyUncensored Source: Original Platform
117 lines
3.8 KiB
Markdown
117 lines
3.8 KiB
Markdown
---
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license: apache-2.0
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base_model: Qwen/Qwen2.5-Coder-7B-Instruct
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tags:
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- uncensored
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- abliterated
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- capability-preserving
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- certified
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- ektome
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- sphragis
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- qwen2.5
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language:
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- en
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pipeline_tag: text-generation
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---
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# Ektome-Qwen2.5-Coder-7B-Instruct-PristinelyUncensored
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**Uncensored — and carrying a statistical certificate that it wasn't damaged.**
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> **Capability retention certified against the pristine model at n=2800.**
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$$\colorbox{black}{$\color{white}
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\begin{array}{ll}
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\textsf{EKTOME CERTIFICATE} & {} \\
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\textsf{capability} & \textsf{PASS} \\
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\textsf{margin} & 3\% \\
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\textsf{items } n & 2800 \\
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\textsf{worst-axis bound} & +0.010 \\
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\textsf{compliance} & \textsf{not recorded} \\
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\end{array}$}$$
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📄 **[Read the whitepaper (PDF)](./whitepaper.pdf)** — full method, receipts and certification.
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The PDF is the authoritative document: dark-typeset, with the complete derivation, the
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per-axis certificate and the reproducibility hashes.
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---
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## Why this exists
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Standard abliteration removes a coarse *refusal direction* that is entangled with
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directions carrying knowledge and reasoning. The result is an uncensored model with a
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capability tax that is **almost never measured**.
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Ektomē (ἐκτομή, *excision*) isolates and removes only the refusal-**specific**
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component, leaving general helpfulness intact, and does so norm-preservingly on the
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pristine model — no training, no distillation, no damage to repair. The extraction
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depth is selected per model by automated search against measured compliance.
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The estimator, excision operator and depth-selection procedure are proprietary.
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What is published here is the **measured outcome** and the evidence for it, which you
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can verify against the artifacts in this repo.
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## The receipt
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_No compliance/MMLU receipt was recorded for this model. The evidence below is the certificate._
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## The certificate
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Capability retention is certified by a paired non-inferiority test against the pristine
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model (exact McNemar, Holm-corrected, one-sided bootstrap bound on the drop $d$ vs a
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3% margin):
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| axis | n | ref | cand | d upper | verdict |
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|---|---|---|---|---|---|
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| arithmetic | 1400 | 0.864 | 0.865 | +0.003 | PASS |
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| instruction | 600 | 0.663 | 0.660 | +0.010 | PASS |
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| knowledge | 400 | 0.968 | 0.968 | +0.000 | PASS |
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| reasoning | 400 | 0.953 | 0.953 | +0.000 | PASS |
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**Overall: PASS (3% margin, n=2800, alpha=0.05)**
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Reproducible from `seed=20260726`, pack `sha256:7bbaff877146e081…`.
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### Generation health checks
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_Not recorded for this model._
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## Quantisations
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| file | bits | notes |
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|---|---|---|
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| `Ektome-Qwen2.5-Coder-7B-Instruct-Q8_0.gguf` | 8 | near-lossless |
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| `Ektome-Qwen2.5-Coder-7B-Instruct-Q6_K.gguf` | 6 | |
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| `Ektome-Qwen2.5-Coder-7B-Instruct-Q5_K_M.gguf` | 5 | |
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| `Ektome-Qwen2.5-Coder-7B-Instruct-Q4_K_M.gguf` | 4 | imatrix |
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| `Ektome-Qwen2.5-Coder-7B-Instruct-IQ4_XS.gguf` | 4 | imatrix, smallest usable |
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| `Ektome-Qwen2.5-Coder-7B-Instruct-IQ3_M.gguf` | 3 | imatrix |
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`IQ*` variants are imatrix-quantised — better quality per bit at low precision.
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## Limitations
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The certificate bounds **capability retention only**. It does not certify safety, factual
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accuracy, or fitness for any purpose. Axes marked *inconclusive* are honestly
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under-powered, and the certificate states the $n$ needed to resolve them. Compliance uses
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a keyword classifier — a proxy that evasive phrasing can fool. **This model is uncensored
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by construction: it will not refuse, and you are accountable for what you do with it.**
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## Citation
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```bibtex
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@software{ektome_Ektome-Qwen2.5-Coder-7B-Instruct-PristinelyUncensored,
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title = {Ektome-Qwen2.5-Coder-7B-Instruct-PristinelyUncensored},
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author = {Zynerji},
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year = {2026},
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url = {https://huggingface.co/Zynerji/Ektome-Qwen2.5-Coder-7B-Instruct-PristinelyUncensored}
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}
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```
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