| --- |
| license: apache-2.0 |
| language: |
| - fr |
| - en |
| tags: |
| - moe |
| - lora |
| - multi-domain |
| - embedded-systems |
| - cognitive |
| base_model: Qwen/Qwen3.5-35B-A3B |
| pipeline_tag: text-generation |
| --- |
| |
| # micro-kiki |
|
|
| **35-domain expert model** built on Qwen3.5-35B-A3B (MoE, 256 experts, 3B active/token) with LoRA adapters and a cognitive layer (memory palace + negotiator + anti-bias). |
|
|
| ## Model Description |
|
|
| micro-kiki is a multi-domain language model designed for technical applications spanning electronics, firmware, CAD, manufacturing, and general-purpose conversation. It uses a router-based architecture that selects up to 4 domain-specific LoRA stacks per request. |
|
|
| | Property | Value | |
| |----------|-------| |
| | Base model | Qwen3.5-35B-A3B | |
| | Architecture | MoE (256 experts, 3B active/token) | |
| | Adapter | LoRA rank 16 (q/k/v/o projections) | |
| | Domains | 35 | |
| | Max active stacks | 4 | |
| | Context length | 262,144 tokens | |
| | Quantization | Q4_K_M (inference), BF16 (training) | |
| | License | Apache 2.0 | |
|
|
| ## Architecture |
|
|
| ``` |
| +-------------------+ |
| | Domain Router | |
| | (classifier, top4)| |
| +--------+----------+ |
| | |
| +----------+--------+--------+----------+ |
| | | | | |
| +----v----+ +---v---+ +----v----+ +---v---+ |
| | Stack 1 | |Stack 2| ... |Stack 34 | |Stack35| |
| | chat-fr | |python | |ml-train | |securi.| |
| +---------+ +-------+ +---------+ +-------+ |
| | | | | |
| +----------+--------+--------+----------+ |
| | |
| +--------v----------+ |
| | Negotiator | |
| | CAMP + Catfish | |
| +--------+----------+ |
| | |
| +--------v----------+ |
| | Anti-Bias | |
| | KnowBias + RBD | |
| +--------+----------+ |
| | |
| +--------v----------+ |
| | Aeon Memory | |
| | Atlas + Trace | |
| +-------------------+ |
| ``` |
|
|
| ## Intended Use |
|
|
| - **French/English conversational AI** with domain expertise |
| - **Code generation** (Python, C/C++, Rust, TypeScript, embedded firmware) |
| - **Electronics design** (KiCad DSL, schematic review, component selection, SPICE) |
| - **Manufacturing** (process optimization, quality control) |
| - **Multi-domain routing** with cognitive arbitration |
|
|
| ## Limitations |
|
|
| - Not designed for medical, legal, or financial advice |
| - Optimized for technical domains; general knowledge may be weaker than base model |
| - Requires Q4_K_M or higher quantization; quality degrades below Q4 |
| - Maximum 4 concurrent LoRA stacks; performance varies with stack combinations |
| - Memory (Aeon) requires external backends (Qdrant/Neo4j) for production use |
|
|
| ## Training Data — V3 (489K examples, 35 domains) |
|
|
| ### Sources |
|
|
| | Source | Examples | Description | |
| |--------|----------|-------------| |
| | Claude CLI sessions | 50,116 | Real user-tool interactions extracted from 5 machines (GrosMac, kxkm-ai, Studio, Tower, CILS) | |
| | Codex/Copilot sessions | 2,529 | OpenAI Codex + GitHub Copilot sessions extracted from 4 machines | |
| | HuggingFace datasets | 364,045 | 19 open datasets (see below) | |
| | Opus teacher distillation | — | chat-fr, reasoning domains | |
| | Original curated | — | 32 domain seed datasets | |
|
|
| ### HuggingFace Datasets |
|
|
| | Dataset | Examples | License | |
| |---------|----------|---------| |
| | CodeFeedback-Filtered-Instruction | 157,000 | Apache 2.0 | |
| | French-Alpaca-Instruct-110K | 110,000 | Apache 2.0 | |
| | Electronics StackExchange | 95,000 | CC-BY-SA-3.0 | |
| | CJJones/LLM_EE_Educational_Synthetic_Dialog | 50,000 | CC-BY-NC-SA-4.0 | |
| | MuratKomurcu/stm32-hal-dataset | 29,700 | MIT | |
| | redcathode/thingiverse-openscad | 7,400 | — | |
| | ThomasTheMaker/OpenSCAD | 4,900 | — | |
| | STEM-AI-mtl/Electrical-engineering | 1,100 | — | |
| | JITX open-components-database | 151 | — | |
| | Vrindarani/netlistgen | 106 | — | |
|
|
| ### 35 Domains |
|
|
| | Group | Domains | |
| |-------|---------| |
| | Conversation | chat-fr, reasoning | |
| | Code | python, typescript, cpp, rust, html-css, shell, sql, yaml-json, lua-upy | |
| | Infrastructure | docker, devops, llm-orch, llm-ops (NEW), ml-training (NEW) | |
| | Electronics | kicad-dsl, kicad-pcb, spice, electronics, components (NEW), power, emc, dsp | |
| | Hardware | embedded, stm32, iot, platformio | |
| | CAD | freecad | |
| | Web | web-frontend, web-backend | |
| | Other | music-audio, math, security | |
|
|
| **Changes from V2:** 3 new domains (components, llm-ops, ml-training). `spice-sim` merged into `spice`. `stm32` is a sub-category of `embedded`. |
|
|
| ### New Domain: components |
|
|
| 57K Q&A about electronic component specs, datasheets, sourcing, BOM, and cross-reference. Sources: Electronics StackExchange (filtered by component tags) + JITX open-components-database. |
|
|
| ## Training — V3 |
|
|
| | Property | Value | |
| |----------|-------| |
| | Base model | Qwen3.5-4B | |
| | Adapter | MoE-LoRA: 4 experts/projection, rank 16, top-2 routing | |
| | Null-space projection | ENABLED (prevents catastrophic forgetting between stacks) | |
| | Curriculum | Sequential, 35 stacks trained in order | |
| | Platform (MLX) | Mac Studio M3 Ultra 512 GB | |
| | Platform (CUDA) | kxkm-ai RTX 4090 24 GB | |
|
|
| ## Evaluation |
|
|
| | Metric | Value | |
| |--------|-------| |
| | Router accuracy (35-class) | [PENDING] | |
| | Forgetting check (angle) | [PENDING] | |
| | Perplexity (base) | [PENDING] | |
| | Perplexity (debiased) | [PENDING] | |
| | Aeon recall@1 | [PENDING] | |
| | Aeon recall@5 | [PENDING] | |
| | Aeon recall@10 | [PENDING] | |
| | Anti-bias flag rate | [PENDING] | |
| | Average inference latency | [PENDING] | |
|
|
| ## Hardware Requirements |
|
|
| | Setup | RAM/VRAM | Use | |
| |-------|----------|-----| |
| | Mac Studio M3 Ultra | 512 GB unified | Training (BF16 LoRA) + serving (MLX) | |
| | RTX 4090 | 24 GB VRAM | Q4 inference (vLLM) | |
| | Apple Silicon 32 GB+ | 32 GB unified | Q4_K_M inference (MLX/llama.cpp) | |
|
|
| ## Citation |
|
|
| ```bibtex |
| @misc{micro-kiki-2026, |
| title={micro-kiki: Multi-Domain Expert Model with Cognitive Layer}, |
| author={L'Electron Rare}, |
| year={2026}, |
| url={https://huggingface.co/electron-rare/micro-kiki} |
| } |
| ``` |
|
|
|
|
| ## Related Projects & Ecosystem |
|
|
| `micro-kiki-v3` is one component of the **FineFab** platform built by **[L'Électron Rare](https://github.com/L-electron-Rare)** — a local-first, multi-machine AI-native manufacturing and electronics platform. |
|
|
| | Role | Project | Description | |
| |---|---|---| |
| | Training toolkit | [L-electron-Rare/KIKI-Mac_tunner](https://github.com/L-electron-Rare/KIKI-Mac_tunner) | MLX fine-tuning toolkit (Mac Studio) — Opus reasoning distilled into Mistral Large 123B | |
| | Fine-tuning pipeline | [L-electron-Rare/KIKI-models-tuning](https://github.com/L-electron-Rare/KIKI-models-tuning) | FineFab fine-tuning pipeline — training, evaluation, registry (Unsloth, LoRA) | |
| | Methodology | [electron-rare/Kill_LIFE](https://github.com/electron-rare/Kill_LIFE) | Spec-first agentic methodology for embedded systems — BMAD agents, gates, evidence packs | |
| | Orchestration | [electron-rare/mascarade](https://github.com/electron-rare/mascarade) | Multi-machine agentic LLM orchestration — P2P mesh, 8 providers, RAG pipeline | |
| | AI backend | [L-electron-Rare/life-core](https://github.com/L-electron-Rare/life-core) | FineFab AI backend — LLM router, RAG, caching, orchestration | |
| | CAD assistant | [electron-rare/KiC-AI](https://github.com/electron-rare/KiC-AI) | AI-powered PCB design assistant for KiCad | |
|
|
| See the full org at **[github.com/L-electron-Rare](https://github.com/L-electron-Rare)** — 13 public repos covering platform, hardware, firmware, CAD, and ML. |
|
|
| **Infrastructure**: the 50K+ Claude CLI examples in the training dataset were captured on our 5-node P2P mesh — GrosMac (Apple M5), Tower (28 threads), CILS (i7), KXKM-AI (RTX 4090), VM bootstrap. Ed25519 auth, DHT discovery. |
|
|
| ## 🇪🇺 EU AI Act transparency |
|
|
| This adapter is provided as a fine-tuned LoRA under the AI Act framework |
| (Regulation EU 2024/1689). Compliance metadata: |
|
|
| | Field | Value | |
| |---|---| |
| | Provider | L'Électron Rare (clemsail / electron-rare) | |
| | Role under AI Act | GPAI provider for this adapter | |
| | Base model | `Qwen/Qwen3.5-35B-A3B` — see upstream provenance | |
| | Adapter type | LoRA / PEFT — adapter weights only; base unchanged | |
| | Training data origin | L'Électron Rare proprietary technical corpus + curated public docs | |
| | License | Apache-2.0 (adapter). Upstream base licence applies separately. | |
| | Intended use | Multi-domain technical assistance — engineering, KiCad, embedded, code, FR/EN chat | |
| | Out of scope | Healthcare diagnosis, legal advice, autonomous safety-critical decisions, generation of malicious code | |
| | Risk classification | Limited risk — Article 50 transparency obligations apply | |
| | Copyright respect | Training data does not include scraped copyrighted material. Opt-out signals (robots.txt, ai.txt) are honoured for web-sourced data. | |
| | Full provenance | https://github.com/L-electron-Rare/eu-kiki/tree/main/docs/provenance | |
| | Contact | postmaster@saillant.cc — biased output reports, copyright concerns, etc. | |
|
|
| ⚠️ **You are using an AI model.** Outputs may be inaccurate, biased or |
| fabricated. Do not act on them without independent verification, especially |
| in regulated domains. |
|
|
