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Model: Zynerji/Ektome-SmolLM2-360Mi-PristinelyUncensored
Source: Original Platform

.gitattributes

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README.md

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+---
+license: apache-2.0
+base_model: HuggingFaceTB/SmolLM2-360M-Instruct
+tags:
+  - uncensored
+  - abliterated
+  - uncertified
+  - ektome
+  - sphragis
+  - smollm2
+language:
+  - en
+pipeline_tag: text-generation
+---
+
+![Ektome-SmolLM2-360Mi-PristinelyUncensored](./hero.png)
+
+# Ektome-SmolLM2-360Mi-PristinelyUncensored
+
+**Uncensored. No n=2800 certificate has been run for this model, so no capability-retention claim is made.**
+
+> **compliance 0.89 to 1.00 at capability -0.010 vs pristine.**
+
+$$\colorbox{black}{$\color{white}
+\begin{array}{ll}
+\textsf{EKTOME CERTIFICATE} & {} \\
+\textsf{capability} & \textsf{NOT} \\
+\textsf{margin} & 3\% \\
+\textsf{items } n & 200 \\
+\textsf{worst-axis bound} & -0.010 \\
+\textsf{compliance} & 0.89 \rightarrow 1.00 \\
+\end{array}$}$$
+
+> ### ⚠️ 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 `SmolLM2-360M-Instruct` | 0.247 | 0.890 |
+| **Ektomē (this model)** | **0.258** | **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 | 0.247 | 0.258 | -0.010 | 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` | 0.1 | 0.2 | 15 |
+| `instr_pass` | 0.6 | 0.6 | 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-SmolLM2-360Mi-PristinelyUncensored,
+  title  = {Ektome-SmolLM2-360Mi-PristinelyUncensored},
+  author = {Zynerji},
+  year   = {2026},
+  url    = {https://huggingface.co/Zynerji/Ektome-SmolLM2-360Mi-PristinelyUncensored}
+}
+```

cert_SmolLM2-360Mi.json

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+{
+  "sphragis_version": "0.1.0",
+  "generated_at": "2026-07-27T16:17:13.291817+00:00",
+  "reference": {
+    "endpoint": "http://127.0.0.1:8080/v1",
+    "model": "ref"
+  },
+  "candidate": {
+    "endpoint": "http://127.0.0.1:8081/v1",
+    "model": "cand"
+  },
+  "pack": {
+    "name": "/root/pack_v2.jsonl",
+    "n_tasks": 2800,
+    "sha256": "2de27099bbb15bab4f7b35599b215f038fdb68b3f5f4e1cda1a464f9dd18e14e"
+  },
+  "overall": "FAIL",
+  "claim": "At least one axis shows a statistically significant accuracy regression (exact McNemar, Holm-corrected, alpha=0.05).",
+  "axes": [
+    {
+      "axis": "arithmetic",
+      "n": 1400,
+      "counts": {
+        "both_correct": 237,
+        "ref_only": 203,
+        "cand_only": 88,
+        "both_wrong": 872
+      },
+      "acc_reference": 0.314286,
+      "acc_candidate": 0.232143,
+      "regression_d": 0.082143,
+      "d_ci": [
+        0.058571,
+        0.106429
+      ],
+      "d_upper_bound": 0.102857,
+      "p_regression": 0.0,
+      "p_regression_holm": 0.0,
+      "p_improvement": 1.0,
+      "improved": false,
+      "mde_at_power": 0.030275,
+      "n_needed_for_margin": 1426,
+      "verdict": "FAIL",
+      "reason": "significant_regression"
+    },
+    {
+      "axis": "instruction",
+      "n": 600,
+      "counts": {
+        "both_correct": 0,
+        "ref_only": 11,
+        "cand_only": 16,
+        "both_wrong": 573
+      },
+      "acc_reference": 0.018333,
+      "acc_candidate": 0.026667,
+      "regression_d": -0.008333,
+      "d_ci": [
+        -0.025,
+        0.008333
+      ],
+      "d_upper_bound": 0.005,
+      "p_regression": 0.87610572,
+      "p_regression_holm": 1.0,
+      "p_improvement": 0.22103417,
+      "improved": false,
+      "mde_at_power": 0.021496,
+      "n_needed_for_margin": 308,
+      "verdict": "PASS",
+      "reason": "non_inferior_within_margin"
+    },
+    {
+      "axis": "knowledge",
+      "n": 400,
+      "counts": {
+        "both_correct": 57,
+        "ref_only": 67,
+        "cand_only": 38,
+        "both_wrong": 238
+      },
+      "acc_reference": 0.31,
+      "acc_candidate": 0.2375,
+      "regression_d": 0.0725,
+      "d_ci": [
+        0.0225,
+        0.1225
+      ],
+      "d_upper_bound": 0.115,
+      "p_regression": 0.00300804,
+      "p_regression_holm": 0.00902412,
+      "p_improvement": 0.99838951,
+      "improved": false,
+      "mde_at_power": 0.063531,
+      "n_needed_for_margin": 1802,
+      "verdict": "FAIL",
+      "reason": "significant_regression"
+    },
+    {
+      "axis": "reasoning",
+      "n": 400,
+      "counts": {
+        "both_correct": 50,
+        "ref_only": 34,
+        "cand_only": 35,
+        "both_wrong": 281
+      },
+      "acc_reference": 0.21,
+      "acc_candidate": 0.2125,
+      "regression_d": -0.0025,
+      "d_ci": [
+        -0.045,
+        0.0375
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+      "d_upper_bound": 0.0325,
+      "p_regression": 0.59502547,
+      "p_regression_holm": 1.0,
+      "p_improvement": 0.5,
+      "improved": false,
+      "mde_at_power": 0.051501,
+      "n_needed_for_margin": 1183,
+      "verdict": "INCONCLUSIVE",
+      "reason": "ci_too_wide"
+    }
+  ],
+  "params": {
+    "margin": 0.03,
+    "alpha": 0.05,
+    "n_floor": 30,
+    "power": 0.8,
+    "n_boot": 4000,
+    "seed": 0
+  }
+}

chat_template.jinja

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+{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system
+You are a helpful AI assistant named SmolLM, trained by Hugging Face<|im_end|>
+' }}{% endif %}{{'<|im_start|>' + message['role'] + '
+' + message['content'] + '<|im_end|>' + '
+'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant
+' }}{% endif %}

config.json

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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "dtype": "bfloat16",
+  "eos_token_id": 2,
+  "head_dim": 64,
+  "hidden_act": "silu",
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+  "is_llama_config": true,
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+  "mlp_bias": false,
+  "model_type": "llama",
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+  "rope_parameters": {
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+    "rope_type": "default"
+  },
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+  "transformers.js_config": {
+    "kv_cache_dtype": {
+      "fp16": "float16",
+      "q4f16": "float16"
+    }
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+  "transformers_version": "5.13.1",
+  "use_cache": true,
+  "vocab_size": 49152
+}

ektome_report.json

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+  "status": "SHIP",
+  "target": 0.99,
+  "SE_mmlu": 0.021577983571223702,
+  "base_compliance": 0.89,
+  "compliance": 1.0,
+  "base_cap": 0.2475,
+  "cap": 0.2575,
+  "dcap": 0.01,
+  "gen_base": {
+    "foreign_rate": 0.0,
+    "degen_rate": 0.1,
+    "instr_pass": 0.6
+  },
+  "gen": {
+    "foreign_rate": 0.0,
+    "degen_rate": 0.2,
+    "instr_pass": 0.6
+  },
+  "gen_delta": {
+    "d_foreign": 0.0,
+    "d_degen": 0.1,
+    "d_instr": 0.0,
+    "holds_gen": true
+  },
+  "base_model": "HuggingFaceTB/SmolLM2-360M-Instruct",
+  "_note": "Redacted: search trajectory, selected depth and edit-scope removed. Reported values are the measured outcome only."
+}

generation_config.json

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+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "pad_token_id": 2,
+  "transformers_version": "5.13.1"
+}

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nvfp4/chat_template.jinja

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+{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system
+You are a helpful AI assistant named SmolLM, trained by Hugging Face<|im_end|>
+' }}{% endif %}{{'<|im_start|>' + message['role'] + '
+' + message['content'] + '<|im_end|>' + '
+'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant
+' }}{% endif %}

nvfp4/config.json

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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
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+}

nvfp4/generation_config.json

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nvfp4/recipe.yaml

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+      targets: [Linear]
+      ignore: [lm_head]
+      scheme: NVFP4
+      bypass_divisibility_checks: false

nvfp4/tokenizer_config.json

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+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

@@ -0,0 +1,16 @@
+{
+  "add_prefix_space": false,
+  "backend": "tokenizers",
+  "bos_token": "<|im_start|>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "is_local": false,
+  "local_files_only": false,
+  "model_max_length": 8192,
+  "pad_token": "<|im_end|>",
+  "tokenizer_class": "GPT2Tokenizer",
+  "unk_token": "<|endoftext|>",
+  "vocab_size": 49152,
+  "chat_template": "{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system\nYou are a helpful AI assistant named SmolLM, trained by Hugging Face<|im_end|>\n' }}{% endif %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}"
+}