| --- |
| license: mit |
| language: |
| - en |
| tags: |
| - governed-language-model |
| - semiconductor |
| - conversational |
| - governance |
| pipeline_tag: text-generation |
| --- |
| |
| # Axiom-560M |
|
|
| **A Governed Language Model — every output ships its own proof of governance.** |
|
|
| Axiom-560M is a dual-mode decoder (conversational + semiconductor) trained on 56,000 governed pairs. Governance isn't a filter — it's the architecture. |
|
|
| ## Model Details |
|
|
| | | | |
| |---|---| |
| | Architecture | BLOOM-560M (decoder-only transformer) | |
| | Parameters | 559M | |
| | Training data | 56,000 governed pairs (conversational + semiconductor RTL) | |
| | Eval loss | 0.1635 | |
| | Perplexity | 1.18 overall (1.16 conversational, 1.64 semiconductor) | |
| | License | MIT | |
|
|
| ## Modes |
|
|
| **Conversational** — governed dialogue (perplexity 1.16) |
|
|
| **Semiconductor** — governed RTL and hardware specifications (perplexity 1.64) |
|
|
| ## Usage |
|
|
| ```python |
| from transformers import AutoModelForCausalLM, AutoTokenizer |
| |
| model = AutoModelForCausalLM.from_pretrained("MetaCortex-Dynamics/Axiom-560M") |
| tokenizer = AutoTokenizer.from_pretrained("MetaCortex-Dynamics/Axiom-560M") |
| |
| input_ids = tokenizer.encode("<|conv|>What is governed generation?", return_tensors="pt") |
| output = model.generate(input_ids, max_new_tokens=200, temperature=0.7, do_sample=True) |
| print(tokenizer.decode(output[0], skip_special_tokens=True)) |
| ``` |
|
|
| ## Governance |
|
|
| Every output passes through a four-phase governance pipeline: |
|
|
| ``` |
| PROPOSE → DECIDE → PROMOTE → EXECUTE |
| ``` |
|
|
| - 15 grounding operators as token vocabulary |
| - 7 interrogative witnesses as grammar |
| - Admissibility gates (G₁-G₇) with three-valued semantics |
| - Machine-verifiable governance trace on every output |
|
|
| ## Links |
|
|
| - [Interactive Demo](https://huggingface.co/spaces/MetaCortex-Dynamics/Axiom-Ref) — try Axiom in your browser |
| - [Source Code](https://github.com/MetaCortex-Dynamics/Axiom) — MIT license |
| - [Benchmark Results](https://github.com/MetaCortex-Dynamics/Axiom/blob/main/BENCHMARKS.md) — 100% governance vs 0% all LLMs |
|
|
| ## Organization |
|
|
| [MetaCortex Dynamics DAO](https://github.com/MetaCortex-Dynamics) |
|
|
