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
micro-kiki stack-chat-fr (MLX adapter, French chat)
Single MLX adapter file (adapters.safetensors, 6.76 GB) plus its iteration-1300
checkpoint (0001300_adapters.safetensors, same size). Published 2026-05-05 as a
"multi-adapter stack for French chat" on top of Qwen/Qwen3.5-35B-A3B.
Provenance warning. No
adapter_config.json, no training log and no eval of this exact file are shipped. Base model, rank, target layers, learning rate and data are therefore not recorded for this artefact; the base model in the frontmatter is the one declared by the original card and could not be verified from files. Prefermicro-kiki-v4-sota/chat-fr(fully documented) for any use.
Recipe
| Parameter | Value |
|---|---|
| Base model (declared) | Qwen/Qwen3.5-35B-A3B |
| Framework | MLX (mlx_lm), BF16 |
| Iterations | ≥ 1300 (from the checkpoint file name) |
| Rank / scale / layers / lr / seq length | not recorded |
| Training data | micro-kiki chat-fr domain (French instruction/chat corpus, incl. Opus-distilled samples); counts not recorded |
Training host & cost
Mac Studio M3 Ultra 512 GB, MLX BF16 (project default). Peak memory, wall-clock, energy: not recorded. Host powered off since 2026-10.
Evaluation
The file evals/chat-fr-164-cross.json kept in this repository reports HumanEval+
(n=164, max_tokens 384) pass@1 = 0.543, total generation 729.7 s — but its own
metadata says it was run with base_model = Qwen3.6-35B-A3B and
adapter = lora-qwen36-35b-v4-sota/chat-fr, i.e. on the V4-SOTA chat-fr adapter, not
on this file. No evaluation of this 6.76 GB adapter is recorded.
June 2026 iact-bench caveat: on Qwen3.6-35B-A3B, the sibling ailiance LoRA family showed
no gain over the base except html-css; no comparable measurement exists for this adapter.
Limitations
Undocumented recipe; research artefact; no safety tuning; not for medical, legal or financial advice.
Citation
micro-kiki concept DOI 10.5281/zenodo.19666759.
Provenance
https://github.com/hypneum-lab/micro-kiki · https://github.com/ailiance/ailiance-mac-tuner
EU AI Act transparency
LoRA adapter weights only, base unchanged; provider Clément Saillant / L'Electron Rare for Hypneum Lab; limited risk, Article 50; contact clement@saillant.cc. Outputs may be inaccurate, biased or fabricated.
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