--- license: apache-2.0 language: - en tags: - mlx - safetensors - bonsai - oqe - calibration-smoke - experimental - not-for-production pipeline_tag: text-generation library_name: mlx base_model: - TiGa-RCE/Bonsai-27B-MLX-BF16-Config-Repaired --- # Bonsai 27B oQ2e S32 Calibration Smoke > **Experimental calibration artifact. Not a quality release. Do not use this > model to judge Bonsai quality or as a production checkpoint.** ## Experiment family and current status This is one public checkpoint in an **unfinished** MLX/oMLX compatibility and quantization experiment: - [BF16 config-repaired archival baseline](https://huggingface.co/TiGa-RCE/Bonsai-27B-MLX-BF16-Config-Repaired) - **oQ2e S32 calibration smoke — this repository** - [oQ4e S32 calibration smoke](https://huggingface.co/TiGa-RCE/Bonsai-27B-oQ4e-S32-Smoke) The experiment remains incomplete until maintained MLX/MLX-LM/oMLX support can load and generate through the relevant Bonsai paths without the current local compatibility patches, explicit calibration proxies, or imatrix-boundary workarounds. The larger predeclared evaluations follow that runtime gate. The Hub's approximately `3B` badge counts packed quantized storage tensors. It does not mean this is a newly trained 3B model; the logical source architecture is Bonsai 27B. This repository preserves the first bounded oQe 2-bit output that loaded and generated normally on a 32 GB Apple Silicon host. Its purpose is reproducible pipeline evidence and storage, not a recommended deployment target. ## What this proves - An oQe-enhanced 2-bit MLX artifact could be produced from the public BF16 conversion baseline and loaded by the local oMLX runtime. - The 32-sample calibration completed with 496 imatrix entries. - On fixed 10-question smoke screens it scored HellaSwag 7/10 and ARC-Challenge 6/10. - Single-request oMLX generation measured 15.71 tok/s at a 1,024-token prompt and 15.44 tok/s at 4,096 tokens, with cache disabled. ## What this does not prove The sensitivity stage was intentionally minimal: 2 samples of 64 tokens. The artifact has not passed the predeclared 100-question evaluations or a quality-sized sensitivity pass. It must not be compared with a validated Q4, Q8, oQ4, or oQ8 checkpoint as though it were a quality result. ## Reproduction Parameters | Setting | Value | | --- | ---: | | oQ level | 2 | | imatrix samples | 32 | | imatrix sequence length | 512 | | sensitivity samples | 2 | | sensitivity sequence length | 64 | | calibration dataset | `oqe_code_multilingual` | | imatrix entries | 496 | `oq_imatrix_report.json`, `PROVENANCE.json`, and the included `IMATRIX_CACHE_SHA256.npz` record the exact emitted artifact and calibration evidence. The NPZ is archival provenance; it is not needed to run the model. ## Provenance - Derived baseline: [TiGa-RCE/Bonsai-27B-MLX-BF16-Config-Repaired](https://huggingface.co/TiGa-RCE/Bonsai-27B-MLX-BF16-Config-Repaired) - Original source: [prism-ml/Bonsai-27B-gguf](https://huggingface.co/prism-ml/Bonsai-27B-gguf) - Source revision: `0cf7e3d21581b169b4df1de8bf01316000e2fbb7` - Original source file SHA-256: `d4a381a6d07131c34af888607bdbda49fc885c97673a0d22aa3e0f0284bba566` - Output model hash manifest: `MODEL_SHA256SUMS.txt` The project retains the upstream Apache-2.0 `LICENSE.txt` and `NOTICE.txt`. ## Attribution Created by Technologies Brewster Jennings du Canada for the Bonsai MLX quantization experiment. Created using Bonsai by Prism ML, derived from Qwen3.6-27B.