upload eu-kiki LoRA adapter

README.md

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+---
+license: apache-2.0
+base_model: mistralai/Devstral-Small-2-24B-Instruct-2512
+tags:
+  - lora
+  - peft
+  - mlx
+  - eu-kiki
+  - eu-ai-act
+language:
+  - fr
+  - en
+library_name: peft
+---
+
+# eu-kiki-devstral-python-lora
+
+LoRA adapter for **mistralai/Devstral-Small-2-24B-Instruct-2512**, part of the [eu-kiki](https://github.com/L-electron-Rare/eu-kiki) project — a 100 % EU-sovereign multi-model LLM serving pipeline. EU AI Act Article 52/53 compliant.
+
+## Performance
+
+**HumanEval+ (Linux EvalPlus, 164 problems, greedy):** base 87.20 / 82.90 → +python −1.20 / −1.80 pts.
+
+## Usage
+
+```python
+from mlx_lm import load
+from mlx_lm.tuner.utils import linear_to_lora_layers
+from huggingface_hub import snapshot_download
+
+base_path = snapshot_download("mistralai/Devstral-Small-2-24B-Instruct-2512")
+adapter_path = snapshot_download("clemsail/eu-kiki-devstral-python-lora")
+
+model, tokenizer = load(base_path)
+linear_to_lora_layers(model, num_layers=32, config={"rank": 16, "alpha": 32})
+model.load_weights(f"{adapter_path}/adapters.safetensors", strict=False)
+```
+
+Or, simpler, fuse and serve via `mlx_lm fuse`:
+
+```bash
+python -m mlx_lm fuse \
+    --model mistralai/Devstral-Small-2-24B-Instruct-2512 \
+    --adapter-path <adapter_path> \
+    --save-path /tmp/eu-kiki-devstral-python-lora-fused \
+    --dequantize
+```
+
+## Training configuration
+
+| Parameter | Value |
+|---|---|
+| Method | LoRA |
+| Rank | 16 |
+| Alpha | 32 |
+| Dropout | 0.05 |
+| Target modules | q_proj, k_proj, v_proj, o_proj |
+| Precision | BF16 |
+| Optimiser | AdamW |
+| Learning rate | 1e-5 |
+| Framework | MLX (`mlx_lm` fork on Apple Silicon) |
+| Hardware | Mac Studio M3 Ultra 512 GB unified memory |
+
+## Provenance & EU AI Act compliance
+
+Datasets used to train this adapter are HF-traceable. Per-source SPDX licenses, download dates, source row counts, and used row counts are documented in:
+
+- [`docs/eu-ai-act-transparency.md`](https://github.com/L-electron-Rare/eu-kiki/blob/main/docs/eu-ai-act-transparency.md) — system-level transparency record (Art. 52/53)
+- [`MODEL_CARD.md`](https://github.com/L-electron-Rare/eu-kiki/blob/main/MODEL_CARD.md) — full evaluation summary across HumanEval+, MT-Bench, GSM8K, KIKI-DSL v3
+- [`eval/results/SUMMARY.md`](https://github.com/L-electron-Rare/eu-kiki/blob/main/eval/results/SUMMARY.md) — per-bench reproducible results
+
+## Risk classification
+
+**Limited risk** (EU AI Act Art. 52). General-purpose AI; not deployed in safety-critical contexts.
+
+## License
+
+Apache 2.0, matching the base model.
+
+## Citation
+
+```bibtex
+@misc{eu-kiki-2026,
+  title  = {eu-kiki: EU-sovereign multi-model LLM serving with HF-traceable LoRA adapters},
+  author = {Saillant, Clément},
+  year   = {2026},
+  url    = {https://github.com/L-electron-Rare/eu-kiki},
+  note   = {Live demo: https://ml.saillant.cc}
+}
+```

adapter_config.json

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+{
+    "adapter_path": "/Users/clems/KIKI-Mac_tunner/output/eu-kiki/devstral-python",
+    "batch_size": 1,
+    "clear_cache_threshold": 0,
+    "config": "/Users/clems/KIKI-Mac_tunner/output/eu-kiki/devstral-python/train_config.yaml",
+    "data": "/Users/clems/KIKI-Mac_tunner/data/micro-kiki/python",
+    "fine_tune_type": "lora",
+    "grad_accumulation_steps": 4,
+    "grad_checkpoint": true,
+    "iters": 500,
+    "learning_rate": 1e-05,
+    "lora_parameters": {
+        "alpha": 32,
+        "dropout": 0.05,
+        "rank": 16,
+        "scale": 2.0
+    },
+    "lr_schedule": null,
+    "mask_prompt": false,
+    "max_seq_length": 2048,
+    "model": "/Users/clems/KIKI-Mac_tunner/models/Devstral-Small-2-24B-Instruct-2512",
+    "num_layers": -1,
+    "optimizer": "adam",
+    "optimizer_config": {
+        "adam": {},
+        "adamw": {},
+        "muon": {},
+        "sgd": {},
+        "adafactor": {}
+    },
+    "project_name": null,
+    "report_to": null,
+    "resume_adapter_file": null,
+    "save_every": 100,
+    "seed": 42,
+    "steps_per_eval": 100,
+    "steps_per_report": 5,
+    "test": false,
+    "test_batches": 500,
+    "train": true,
+    "val_batches": 10
+}

adapters.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:0b2e643251c9072c406b98f8a2c665bde14a84aa0e9a890ca3b7c0618c6098c8
+size 369693523