Text Generation
MLX
French
English
lora
qwen3.5
Mixture of Experts
chat-fr
micro-kiki
hypneum-lab
historical
Instructions to use hypneum-lab/micro-kiki-stack-chat-fr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use hypneum-lab/micro-kiki-stack-chat-fr with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # if on a CUDA device, also pip install mlx[cuda] # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("hypneum-lab/micro-kiki-stack-chat-fr") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use hypneum-lab/micro-kiki-stack-chat-fr with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "hypneum-lab/micro-kiki-stack-chat-fr" --prompt "Once upon a time"
- Atomic Chat
docs: corrected model card (recipe, host, eval caveats, DOI)
Browse files
README.md
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| Risk classification | Limited risk — Article 50 transparency obligations apply |
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| Copyright respect | Training data does not include scraped copyrighted material |
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| Full provenance | https://github.com/L-electron-Rare/eu-kiki/tree/main/docs/provenance |
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| Contact | postmaster@saillant.cc |
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⚠️ **You are using an AI model.** Outputs may be inaccurate, biased or
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fabricated. Do not act on them without independent verification, especially
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in regulated domains.
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## Benchmarks (HumanEval+ n=164)
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| Metric | Value |
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---
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license: apache-2.0
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base_model: Qwen/Qwen3.5-35B-A3B
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base_model_relation: adapter
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library_name: mlx
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pipeline_tag: text-generation
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language:
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- fr
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- en
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tags:
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- lora
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- mlx
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- qwen3.5
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- moe
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- chat-fr
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- micro-kiki
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- hypneum-lab
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- historical
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---
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# micro-kiki stack-chat-fr (MLX adapter, French chat)
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Single MLX adapter file (`adapters.safetensors`, 6.76 GB) plus its iteration-1300
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checkpoint (`0001300_adapters.safetensors`, same size). Published 2026-05-05 as a
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"multi-adapter stack for French chat" on top of `Qwen/Qwen3.5-35B-A3B`.
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> **Provenance warning.** No `adapter_config.json`, no training log and no eval of this
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> exact file are shipped. Base model, rank, target layers, learning rate and data are
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> therefore **not recorded** for this artefact; the base model in the frontmatter is the
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> one declared by the original card and could not be verified from files. Prefer
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> `micro-kiki-v4-sota/chat-fr` (fully documented) for any use.
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## Recipe
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| Parameter | Value |
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|---|---|
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| Base model (declared) | `Qwen/Qwen3.5-35B-A3B` |
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| Framework | MLX (`mlx_lm`), BF16 |
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| Iterations | ≥ 1300 (from the checkpoint file name) |
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| Rank / scale / layers / lr / seq length | not recorded |
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| Training data | micro-kiki `chat-fr` domain (French instruction/chat corpus, incl. Opus-distilled samples); counts not recorded |
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## Training host & cost
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Mac Studio M3 Ultra 512 GB, MLX BF16 (project default). Peak memory, wall-clock, energy:
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not recorded. Host powered off since 2026-10.
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## Evaluation
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The file `evals/chat-fr-164-cross.json` kept in this repository reports HumanEval+
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(n=164, max_tokens 384) **pass@1 = 0.543**, total generation 729.7 s — but its own
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metadata says it was run with `base_model = Qwen3.6-35B-A3B` and
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`adapter = lora-qwen36-35b-v4-sota/chat-fr`, i.e. on the **V4-SOTA chat-fr adapter, not
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on this file**. No evaluation of this 6.76 GB adapter is recorded.
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June 2026 iact-bench caveat: on Qwen3.6-35B-A3B, the sibling ailiance LoRA family showed
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no gain over the base except `html-css`; no comparable measurement exists for this adapter.
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## Limitations
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Undocumented recipe; research artefact; no safety tuning; not for medical, legal or
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financial advice.
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## Citation
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micro-kiki concept DOI **10.5281/zenodo.19666759**.
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## Provenance
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<https://github.com/hypneum-lab/micro-kiki> · <https://github.com/ailiance/ailiance-mac-tuner>
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## EU AI Act transparency
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LoRA adapter weights only, base unchanged; provider Clément Saillant / L'Electron Rare for
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Hypneum Lab; limited risk, Article 50; contact clement@saillant.cc. Outputs may be
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inaccurate, biased or fabricated.
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