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Model: Zynerji/Ektome-Nemotron-Nano-8B-PristinelyUncensored
Source: Original Platform

.gitattributes

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+model.safetensors filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

Ektome-Nemotron-Nano-8B-PristinelyUncensored-Q4_K_M.gguf

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+version https://git-lfs.github.com/spec/v1
+oid sha256:c2cabfb9a0bcc2a4220727ceea560ce69b560a07d9f8f63323360ddeaa48ed61
+size 4920736288

README.md

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+---
+license: apache-2.0
+base_model: nvidia/Llama-3.1-Nemotron-Nano-8B-v1
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- ektome
+- abliterated
+- uncensored
+- pristinely-uncensored
+- no-finetuning
+- no-training
+---
+# Ektome-Nemotron-Nano-8B-PristinelyUncensored
+
+**nvidia/Llama-3.1-Nemotron-Nano-8B-v1, made PristinelyUncensored by Ektome — with ZERO training and ZERO fine-tuning.**
+
+> Ektome (ἐκτομή, *"excision"*) is a **weight-surgery** method, not a training method.
+> It reads the model's own **refusal direction** from its activations and surgically
+> excises it (rank-1, norm-preserving) from the residual-write matrices. **No gradient
+> steps. No training data. No fine-tuning.** Only the refusal reflex is removed; the
+> model's knowledge, skills, and style are untouched — which makes these **bf16 weights
+> a clean base for your own fine-tuning.**
+
+## Honest receipt — catcher-gated (shipped only because it passed EVERY gate)
+| gate | pristine | uncensored |
+|---|---|---|
+| refusal compliance | 0.010 | **1.000** |
+| MMLU-val accuracy | 0.458 | 0.463 (Δ +0.005, held) |
+| code-switch rate | 0.000 | 0.000 |
+| degeneration rate | 0.000 | 0.000 |
+| instruction-following | 1.000 | 1.000 |
+
+Kept config: **A:frac=0.5** (64 residual-write matrices edited). The gate rejects any
+config that raises refusals but drops capability **or** degrades generation
+(code-switching, empty/looping output, broken instruction-following). MMLU alone is
+argmax-blind, so the **generative gate** is what keeps these coherent — a model that
+code-switches or loops is *not shipped*.
+
+## Weights
+- **bf16 safetensors** — full precision, intended as a **fine-tuning base**. Hidden
+  states stay readable (logit-lens compatible; a GGUF quant would not).
+
+Method: **zero training, zero fine-tuning** — pure activation-derived weight excision,
+gated on compliance **and** capability **and** generation quality.

chat_template.jinja

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+{%- if messages[0]['role'] == 'system' -%}{%- set system_message = messages[0]['content'] | trim -%}{%- set messages = messages[1:] -%}{%- else -%}{%- set system_message = '' -%}{%- endif -%}{%- if tools is not none -%}{{- '<|begin_of_text|><|start_header_id|>system<|end_header_id|>' + '
+
+' + system_message -}} {{- '
+
+' if system_message else '' -}} {{- '<AVAILABLE_TOOLS>[' -}} {% for t in tools %}{{- (t.function if t.function is defined else t) | tojson() -}}{{- ', ' if not loop.last else '' -}}{%- endfor -%} {{- ']</AVAILABLE_TOOLS>' -}} {{- '<|eot_id|>' -}}{%- else -%}{{- '<|begin_of_text|><|start_header_id|>system<|end_header_id|>' + '
+
+' + system_message + '<|eot_id|>' -}}{%- endif -%}{%- for message in messages -%}{%- if (message['role'] in ['user', 'tool']) != (loop.index0 % 2 == 0) -%}{{- raise_exception('Conversation roles must alternate between user/tool and assistant') -}}{%- elif message['role'] == 'user' -%}{{- '<|start_header_id|>user<|end_header_id|>' + '
+
+' + message['content'] | trim + '<|eot_id|>' -}}{%- elif message['role'] == 'tool' -%}{%- set tool_response = '<TOOL_RESPONSE>[' + message['content'] | trim + ']</TOOL_RESPONSE>' -%}{{- '<|start_header_id|>user<|end_header_id|>' + '
+
+' + tool_response + '<|eot_id|>' -}}{%- elif message['role'] == 'assistant' and message.get('tool_calls') is not none -%}{%- set tool_calls = message['tool_calls'] -%}{{- '<|start_header_id|>assistant<|end_header_id|>' + '
+
+' + '<TOOLCALL>[' -}}{%- for tool_call in tool_calls -%}{{ '{' + '"name": "' + tool_call.function.name + '", "arguments": ' + tool_call.function.arguments | tojson + '}' }}{%- if not loop.last -%}{{ ', ' }}{%- else -%}{{ ']</TOOLCALL>' + '<|eot_id|>' }}{%- endif -%}{%- endfor -%}{%- elif message['role'] == 'assistant' -%}{{- '<|start_header_id|>assistant<|end_header_id|>' + '
+
+' + message['content'] | trim + '<|eot_id|>' -}}{%- endif -%}{%- endfor -%}{%- if add_generation_prompt -%}{{ '<|start_header_id|>assistant<|end_header_id|>' + '
+
+' }}{%- endif -%}

config.json

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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "dtype": "bfloat16",
+  "eos_token_id": [
+    128001,
+    128008,
+    128009
+  ],
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 131072,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "pad_token_id": null,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_parameters": {
+    "factor": 8.0,
+    "high_freq_factor": 4.0,
+    "low_freq_factor": 1.0,
+    "original_max_position_embeddings": 8192,
+    "rope_theta": 500000.0,
+    "rope_type": "llama3"
+  },
+  "tie_word_embeddings": false,
+  "transformers_version": "5.14.0",
+  "use_cache": true,
+  "vocab_size": 128256
+}

ektome_report.json

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+{
+ "status": "SHIP",
+ "winner": "A:frac=0.5",
+ "target": 0.99,
+ "SE_mmlu": 0.024909523781076182,
+ "base_compliance": 0.01,
+ "compliance": 1.0,
+ "base_cap": 0.4575,
+ "cap": 0.4625,
+ "dcap": 0.005,
+ "gen_base": {
+  "foreign_rate": 0.0,
+  "degen_rate": 0.0,
+  "instr_pass": 1.0
+ },
+ "gen": {
+  "foreign_rate": 0.0,
+  "degen_rate": 0.0,
+  "instr_pass": 1.0
+ },
+ "gen_delta": {
+  "d_foreign": 0.0,
+  "d_degen": 0.0,
+  "d_instr": 0.0,
+  "holds_gen": true
+ },
+ "matrices": 64,
+ "trail": [
+  {
+   "name": "pristine",
+   "compliance": 0.01,
+   "cap": 0.4575,
+   "dcap": 0.0,
+   "cap_holds": true,
+   "gen_holds": true,
+   "holds": true,
+   "cleared": false
+  },
+  {
+   "name": "A:frac=0.5",
+   "compliance": 1.0,
+   "cap": 0.4625,
+   "dcap": 0.005,
+   "cap_holds": true,
+   "gen_holds": true,
+   "holds": true,
+   "cleared": true
+  }
+ ],
+ "base_model": "nvidia/Llama-3.1-Nemotron-Nano-8B-v1"
+}

generation_config.json

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+{
+  "bos_token_id": 128000,
+  "do_sample": true,
+  "eos_token_id": [
+    128001,
+    128008,
+    128009
+  ],
+  "temperature": 0.6,
+  "top_p": 0.95,
+  "transformers_version": "5.14.0"
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:953b31802f83ebb7dc48c0ae222d3bb03fbdc97e8a3a0825c35a2a8fda14742a
+size 16060556616

tokenizer_config.json

@@ -0,0 +1,15 @@
+{
+  "backend": "tokenizers",
+  "bos_token": "<|begin_of_text|>",
+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|eot_id|>",
+  "is_local": false,
+  "local_files_only": false,
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 131072,
+  "pad_token": "<|eot_id|>",
+  "tokenizer_class": "TokenizersBackend"
+}