from mlx_lm import load, generate

model, tokenizer = load(
    "lmstudio-community/gemma-4-E4B-it-MLX-4bit",
    adapter_path="Ailiance-fr/gemma-4-E4B-aggro-test-lora",
)

print(generate(model, tokenizer, prompt="..."))

Benchmark on production tasks

Gemma aggressive-LR test run — evaluated through the electron-bench functional pipeline (Phases P1 → P6, base vs LoRA).

Task	Result
status	experimental

Full base-vs-LoRA matrix (all phases, all adapters): compare_base_vs_lora.md.

License chain

Component	License
Base model weights (`lmstudio-community/gemma-4-E4B-it-MLX-4bit`)	Gemma Terms of Use
Training data (`Ailiance-fr/kill-life-embedded-qa`)	cc-by-sa-4.0
LoRA adapter (this repo)	CC-BY-SA-4.0

Rationale: weights of the base model inherit from the Gemma Terms of Use, but the LoRA adapter is a derivative of CC-BY-SA-4.0 training data and is therefore released under CC-BY-SA-4.0 (share-alike propagates). Downstream users who load this adapter against the Gemma base must comply with both licenses simultaneously.

Training data lineage

Primary corpus: Ailiance-fr/kill-life-embedded-qa (cc-by-sa-4.0). See the Ailiance-fr catalog for related cards.

EU AI Act compliance

Article 53(1)(c): training data licenses preserved upstream.
Article 53(1)(d): training data summary — see dataset cards on Ailiance-fr.
GPAI Code of Practice (July 2025): base model Gemma (Google is a signatory).
No web scraping by Ailiance, no licensed data, no PII.

License

LoRA weights: CC-BY-SA-4.0 (training-data share-alike). Base model weights remain under Gemma Terms of Use.

Citation

bibtex

@misc{ailiance_gemma_4_E4B_aggro_test_lora_2026,
  author    = {Ailiance},
  title     = {Ailiance — Gemma 4 E4B aggro-test LoRA},
  year      = {2026},
  publisher = {Hugging Face},
  url       = {https://huggingface.co/Ailiance-fr/gemma-4-E4B-aggro-test-lora}
}

See the full Ailiance-fr LoRA collection.

Bench comparison (2026-05-11)

kicad-pcb generation (phase4/5 composite, 5 ref circuits)

Variant	composite	parse_ok	erc_clean	erc_low_warn
gemma-4-E4B base	0.060	0	0	0
This LoRA (tuned)	0.060	0	0	0
Delta	0.000	0	0	0

Note: all parse_ok=0 — domain transfer pcb→sch fails on every variant. The floor reflects the composite formula weights (0.30·parse + 0.40·no-extra-errs + 0.30·no-extra-warns), not actual valid generation.

Source: https://github.com/ailiance/ailiance-bench/blob/main/bench-results/kicad_phase4_lora.json

Ailiance-fr/gemma-4-E4B-aggro-test-lora

Ailiance — Gemma 4 E4B aggro-test LoRA

Quick start (MLX)