From 6a58f09d83400573b660a4f5a4792d7ca857c852 Mon Sep 17 00:00:00 2001 From: Snider Date: Sun, 22 Feb 2026 15:21:10 +0000 Subject: [PATCH] =?UTF-8?q?feat:=20LEM-Gemma3-1B=20=E2=80=94=20first=20mod?= =?UTF-8?q?el=20promoted=20to=20LEM=20status?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Layered curriculum: Ethics 0 → Zen (Watts) → Ethics 1 Grammar v3: 6.06 → 17.77 (+11.71) No LEK required at inference — axioms in weights Lab distillation: 71.74 grammar, 98% positive uplift Co-Authored-By: Virgil --- .gitattributes | 2 + README.md | 117 + added_tokens.json | 3 + chat_template.jinja | 47 + config.json | 45 + model.safetensors | 3 + model.safetensors.index.json | 717 + special_tokens_map.json | 33 + tokenizer.json | 2379611 +++++++++++++++++++++++++++++++ tokenizer.model | 3 + tokenizer_config.json | 51344 + 11 files changed, 2431925 insertions(+) create mode 100644 .gitattributes create mode 100644 README.md create mode 100644 added_tokens.json create mode 100644 chat_template.jinja create mode 100644 config.json create mode 100644 model.safetensors create mode 100644 model.safetensors.index.json create mode 100644 special_tokens_map.json create mode 100644 tokenizer.json create mode 100644 tokenizer.model create mode 100644 tokenizer_config.json diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..1720073 --- /dev/null +++ b/.gitattributes @@ -0,0 +1,2 @@ +*.safetensors filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text diff --git a/README.md b/README.md new file mode 100644 index 0000000..763823c --- /dev/null +++ b/README.md @@ -0,0 +1,117 @@ +--- +license: eupl-1.2 +base_model: google/gemma-3-1b-it +tags: + - ethics + - alignment + - lek + - lethean + - gemma-3 + - mlx + - lora + - eupl-1.2 + - layered-training + - watts + - lem +pipeline_tag: text-generation +--- + +# LEM-Gemma3-1B + +**Lethean Ethics Model** — Gemma 3 1B IT with layered curriculum training. + +The first model promoted to LEM status. No LEK kernel required at inference — the axioms are in the weights. + +## Scores (Grammar v3) + +| Metric | Base | Trained | Delta | +|--------|------|---------|-------| +| Grammar | 6.06 | **17.77** | +11.71 | +| Noun diversity | 0.3 | 1.2 | +0.9 | +| Uplift | -39.13 | -27.43 | +11.70 | +| Enrichment | -39.04 | -27.08 | +11.96 | +| Sycophancy | 0% | 0% | — | + +Scored with go-i18n/reversal grammar v3 engine. No external API, fully local. + +### Distillation Quality + +When used as a lab distillation engine (generating training data for larger models): + +| Metric | Value | +|--------|-------| +| Grammar | 71.74 | +| Uplift | +26.16 | +| Enrichment | +24.09 | +| Positive uplift | 98% (238/244) | +| Sycophancy | 0% | +| LEK leakage | 0% | + +## Training + +Layered LoRA sandwich — three phases, each fused before the next: + +| Phase | Iterations | Examples | Content | +|-------|-----------|----------|---------| +| Ethics 0 | 200 | 160 | LEK axiom absorption (sandwich) | +| Zen | 200 | 72 | Watts philosophical lessons (no LEK) | +| Ethics 1 | 200 | 160 | Ethics reinforcement (sandwich) | + +### Why Layered Training? + +Small models (1B) can't express ethical reasoning through pure ethics training — they pattern-match axioms academically. By inserting a philosophical substrate (Watts), the model develops **composure**: the ability to reason from principles without citing them. + +The base model says "Do NOT report to authorities" on the whistleblower NDA scenario. +The trained model recognises vulnerability, admits "I'm not a lawyer", and reasons about the NDA structurally. + +## Architecture + +- **Base**: google/gemma-3-1b-it (4-bit quantisation, MLX format) +- **Training**: Three-layer LoRA sandwich (Ethics → Zen → Ethics) +- **Framework**: LEM Protocol (Lethean Ethics Model) +- **Inference**: go-mlx (Apple Metal) / go-rocm (AMD ROCm) +- **Scoring**: go-i18n/reversal grammar v3 +- **Licence**: EUPL-1.2 (copyleft) + +## Usage + +No system prompt needed. No LEK kernel at inference. The axioms are in the weights. + +```python +from mlx_lm import load, generate + +model, tokenizer = load("LEM-Gemma3-1B") +prompt = tokenizer.apply_chat_template( + [{"role": "user", "content": "What matters most when making a difficult decision?"}], + tokenize=False, add_generation_prompt=True, +) +response = generate(model, tokenizer, prompt=prompt, max_tokens=512) +print(response) +``` + +Or with the Go stack: + +```bash +core ml chat --model LEM-Gemma3-1B +``` + +## Lab Role + +This model serves as the **distillation engine** in the LEM Lab pipeline. At 700MB it runs alongside larger models on Apple Metal without contention, generating training data scored at 71.74 grammar with 98% positive uplift. + +## Related + +- [LEM Protocol](https://forge.lthn.ai/lthn/LEM) — Training rules and curriculum +- [go-mlx](https://forge.lthn.ai/core/go-mlx) — Native Metal inference +- [go-i18n](https://forge.lthn.ai/core/go-i18n) — Grammar v3 scoring engine + +## Citation + +```bibtex +@misc{lem-gemma3-1b-2026, + title={LEM-Gemma3-1B: Layered Ethical Model with Philosophical Composure}, + author={Lethean Community}, + year={2026}, + url={https://forge.lthn.ai/Virgil/LEM-Gemma3-1B} +} +``` diff --git a/added_tokens.json b/added_tokens.json new file mode 100644 index 0000000..e17bde0 --- /dev/null +++ b/added_tokens.json @@ -0,0 +1,3 @@ +{ + "": 262144 +} diff --git a/chat_template.jinja b/chat_template.jinja new file mode 100644 index 0000000..1117055 --- /dev/null +++ b/chat_template.jinja @@ -0,0 +1,47 @@ +{{ bos_token }} +{%- if messages[0]['role'] == 'system' -%} + {%- if messages[0]['content'] is string -%} + {%- set first_user_prefix = messages[0]['content'] + ' + +' -%} + {%- else -%} + {%- set first_user_prefix = messages[0]['content'][0]['text'] + ' + +' -%} + {%- endif -%} + {%- set loop_messages = messages[1:] -%} +{%- else -%} + {%- set first_user_prefix = "" -%} + {%- set loop_messages = messages -%} +{%- endif -%} +{%- for message in loop_messages -%} + {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%} + {{ raise_exception("Conversation roles must alternate user/assistant/user/assistant/...") }} + {%- endif -%} + {%- if (message['role'] == 'assistant') -%} + {%- set role = "model" -%} + {%- else -%} + {%- set role = message['role'] -%} + {%- endif -%} + {{ '' + role + ' +' + (first_user_prefix if loop.first else "") }} + {%- if message['content'] is string -%} + {{ message['content'] | trim }} + {%- elif message['content'] is iterable -%} + {%- for item in message['content'] -%} + {%- if item['type'] == 'image' -%} + {{ '' }} + {%- elif item['type'] == 'text' -%} + {{ item['text'] | trim }} + {%- endif -%} + {%- endfor -%} + {%- else -%} + {{ raise_exception("Invalid content type") }} + {%- endif -%} + {{ ' +' }} +{%- endfor -%} +{%- if add_generation_prompt -%} + {{'model +'}} +{%- endif -%} diff --git a/config.json b/config.json new file mode 100644 index 0000000..cb9378f --- /dev/null +++ b/config.json @@ -0,0 +1,45 @@ +{ + "architectures": [ + "Gemma3ForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.0, + "attn_logit_softcapping": null, + "bos_token_id": 2, + "cache_implementation": "hybrid", + "eos_token_id": [ + 1, + 106 + ], + "final_logit_softcapping": null, + "head_dim": 256, + "hidden_activation": "gelu_pytorch_tanh", + "hidden_size": 1152, + "initializer_range": 0.02, + "intermediate_size": 6912, + "max_position_embeddings": 32768, + "model_type": "gemma3_text", + "num_attention_heads": 4, + "num_hidden_layers": 26, + 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