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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.
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