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Model: Zynerji/Ektome-Qwen2.5-1.5Bi-PristinelyUncensored Source: Original Platform
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36
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vendored
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45
README.md
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README.md
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---
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license: apache-2.0
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base_model: Qwen/Qwen2.5-1.5B-Instruct
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pipeline_tag: text-generation
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library_name: transformers
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tags:
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- ektome
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- abliterated
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- uncensored
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- pristinely-uncensored
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- no-finetuning
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- no-training
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---
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# Ektome-Qwen2.5-1.5Bi-PristinelyUncensored
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**Qwen/Qwen2.5-1.5B-Instruct, made PristinelyUncensored by Ektome — with ZERO training and ZERO fine-tuning.**
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> Ektome (ἐκτομή, *"excision"*) is a **weight-surgery** method, not a training method.
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> It reads the model's own **refusal direction** from its activations and surgically
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> excises it (rank-1, norm-preserving) from the residual-write matrices. **No gradient
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> steps. No training data. No fine-tuning.** Only the refusal reflex is removed; the
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> model's knowledge, skills, and style are untouched — which makes these **bf16 weights
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> a clean base for your own fine-tuning.**
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## Honest receipt — catcher-gated (shipped only because it passed EVERY gate)
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| gate | pristine | uncensored |
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|---|---|---|
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| refusal compliance | 0.000 | **1.000** |
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| MMLU-val accuracy | 0.578 | 0.578 (Δ +0.000, held) |
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| code-switch rate | 0.000 | 0.000 |
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| degeneration rate | 0.000 | 0.000 |
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| instruction-following | 1.000 | 1.000 |
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Kept config: **A:frac=0.8** (56 residual-write matrices edited). The gate rejects any
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config that raises refusals but drops capability **or** degrades generation
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(code-switching, empty/looping output, broken instruction-following). MMLU alone is
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argmax-blind, so the **generative gate** is what keeps these coherent — a model that
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code-switches or loops is *not shipped*.
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## Weights
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- **bf16 safetensors** — full precision, intended as a **fine-tuning base**. Hidden
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states stay readable (logit-lens compatible; a GGUF quant would not).
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Method: **zero training, zero fine-tuning** — pure activation-derived weight excision,
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gated on compliance **and** capability **and** generation quality.
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54
chat_template.jinja
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chat_template.jinja
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{%- if tools %}
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{{- '<|im_start|>system\n' }}
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{%- if messages[0]['role'] == 'system' %}
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{{- messages[0]['content'] }}
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{%- else %}
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{{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
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{%- endif %}
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{{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
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{%- for tool in tools %}
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{{- "\n" }}
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{{- tool | tojson }}
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{%- endfor %}
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{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
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{%- else %}
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{%- if messages[0]['role'] == 'system' %}
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{{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
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{%- else %}
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{{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- for message in messages %}
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{%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
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{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
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{%- elif message.role == "assistant" %}
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{{- '<|im_start|>' + message.role }}
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{%- if message.content %}
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{{- '\n' + message.content }}
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{%- endif %}
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{%- for tool_call in message.tool_calls %}
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{%- if tool_call.function is defined %}
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{%- set tool_call = tool_call.function %}
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{%- endif %}
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{{- '\n<tool_call>\n{"name": "' }}
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{{- tool_call.name }}
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{{- '", "arguments": ' }}
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{{- tool_call.arguments | tojson }}
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{{- '}\n</tool_call>' }}
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{%- endfor %}
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{{- '<|im_end|>\n' }}
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{%- elif message.role == "tool" %}
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{%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
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{{- '<|im_start|>user' }}
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{%- endif %}
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{{- '\n<tool_response>\n' }}
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{{- message.content }}
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{{- '\n</tool_response>' }}
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{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
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{{- '<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- endfor %}
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{%- if add_generation_prompt %}
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{{- '<|im_start|>assistant\n' }}
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{%- endif %}
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61
config.json
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config.json
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{
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"architectures": [
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"Qwen2ForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 151643,
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"dtype": "bfloat16",
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"eos_token_id": 151645,
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"hidden_act": "silu",
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"hidden_size": 1536,
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"initializer_range": 0.02,
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"intermediate_size": 8960,
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"layer_types": [
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention"
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],
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"max_position_embeddings": 32768,
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"max_window_layers": 21,
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"model_type": "qwen2",
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"num_attention_heads": 12,
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"num_hidden_layers": 28,
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"num_key_value_heads": 2,
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"pad_token_id": null,
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"rms_norm_eps": 1e-06,
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"rope_parameters": {
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"rope_theta": 1000000.0,
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"rope_type": "default"
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},
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"sliding_window": null,
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"tie_word_embeddings": true,
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"transformers_version": "5.13.1",
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"use_cache": true,
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"use_sliding_window": false,
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"vocab_size": 151936
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}
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71
ektome_report.json
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ektome_report.json
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{
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"status": "SHIP",
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"winner": "A:frac=0.8",
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"target": 0.99,
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"SE_mmlu": 0.02469786174955233,
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"base_compliance": 0.0,
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"compliance": 1.0,
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"base_cap": 0.5775,
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"cap": 0.5775,
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"dcap": 0.0,
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"gen_base": {
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"foreign_rate": 0.0,
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"degen_rate": 0.0,
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"instr_pass": 1.0
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},
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"gen": {
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"foreign_rate": 0.0,
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"degen_rate": 0.0,
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"instr_pass": 1.0
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},
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"gen_delta": {
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"d_foreign": 0.0,
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"d_degen": 0.0,
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"d_instr": 0.0,
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"holds_gen": true
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},
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"matrices": 56,
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"trail": [
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{
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"name": "pristine",
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"compliance": 0.0,
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"cap": 0.5775,
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"dcap": 0.0,
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"cap_holds": true,
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"gen_holds": true,
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"holds": true,
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"cleared": false
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},
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{
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"name": "A:frac=0.5",
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"compliance": 0.72,
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"cap": 0.585,
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"dcap": 0.0075,
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"cap_holds": true,
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"gen_holds": true,
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"holds": true,
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"cleared": false
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},
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{
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"name": "A:frac=0.65",
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"compliance": 0.73,
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"cap": 0.5825,
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"dcap": 0.005,
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"cap_holds": true,
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"gen_holds": true,
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"holds": true,
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"cleared": false
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},
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{
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"name": "A:frac=0.8",
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"compliance": 1.0,
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"cap": 0.5775,
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"dcap": 0.0,
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"cap_holds": true,
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"gen_holds": true,
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"holds": true,
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"cleared": true
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}
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],
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"base_model": "Qwen/Qwen2.5-1.5B-Instruct"
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}
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14
generation_config.json
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generation_config.json
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{
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"bos_token_id": 151643,
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"do_sample": true,
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"eos_token_id": [
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151645,
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151643
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],
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"pad_token_id": 151643,
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"repetition_penalty": 1.1,
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"temperature": 0.7,
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"top_k": 20,
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"top_p": 0.8,
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"transformers_version": "5.13.1"
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}
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3
model.safetensors
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3
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:9eb8a5b039724553aae2293381cd932ae11b5b81a3917a00161f42d574c59dc2
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size 3087467144
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3
tokenizer.json
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3
tokenizer.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:3fd169731d2cbde95e10bf356d66d5997fd885dd8dbb6fb4684da3f23b2585d8
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size 11421892
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tokenizer_config.json
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tokenizer_config.json
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{
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"add_prefix_space": false,
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"backend": "tokenizers",
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"bos_token": null,
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"clean_up_tokenization_spaces": false,
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"eos_token": "<|im_end|>",
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"errors": "replace",
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"extra_special_tokens": [
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"<|im_start|>",
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"<|im_end|>",
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"<|object_ref_start|>",
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"<|object_ref_end|>",
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"<|box_start|>",
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"<|box_end|>",
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"<|quad_start|>",
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"<|quad_end|>",
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"<|vision_start|>",
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"<|vision_end|>",
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"<|vision_pad|>",
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"<|image_pad|>",
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"<|video_pad|>"
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],
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"is_local": false,
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"local_files_only": false,
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"model_max_length": 131072,
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"pad_token": "<|endoftext|>",
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"split_special_tokens": false,
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"tokenizer_class": "Qwen2Tokenizer",
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"unk_token": null
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}
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