Instructions to use mpuig/system-one-minicpm5-2b-q8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mpuig/system-one-minicpm5-2b-q8 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download mpuig/system-one-minicpm5-2b-q8 --local-dir system-one-minicpm5-2b-q8
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
system-one-minicpm5-2b-q8 — quality-tier System One model (8-bit)
MiniCPM5-2B-Base (Apache-2.0) fine-tuned with the system-one frozen recipe, LoRA-fused and quantized to 8 bits with MLX (8.501 bits/weight, 2.5 GB). A System One decision model: typed questions (choice / score / noul) over a JSON state, answered with calibrated probabilities from one forward pass — no generation. Part of system-one, an open learning project rebuilding the behavior of Typesafe's Jev. Not affiliated with or endorsed by TypeSafe.
Files
- fused, 8-bit quantized model (MLX format; load with
--model <dir>, no adapter) temperature.json— per-primitive temperatures (choice 0.961 / noul 1.073 / score 1.387), fitted under this exact quantized identity and bound to these weights — the serving engine fails closed on any mismatch.- the unquantized LoRA adapter is published alongside for retraining/re-fusing.
Training and quantization
Same frozen recipe as the volume tier (public recasts + synthetic scenarios teacher-scored by pinned jev-1.13.0 — disclosed deliberately — with overconfidence filtering; readout CE + RPS loss, LR 1e-5, seed 42). Quantization was gate-checked: zero argmax flips across the drift battery, dev quality within noise of BF16, median 1.61x serving speedup. 4-bit was measured and rejected (quality loss, no speed gain over 8-bit on Apple Silicon).
Evaluation (full protocol and CIs in the repo)
| Split | Accuracy | ECE | Notes |
|---|---|---|---|
| Development (n=1,128, calibrated) | 86.6% | 0.019 | used for steering; optimistic |
| Fresh out-of-family test (n=1,048, spent once) | 73.3% | 0.080 | +6.8 pts over the 0.6B tier, CI [+4.5, +9.2]; NLL/Brier also significantly better |
Per primitive (dev): choice 94.2 / noul 90.0 / score 65.9. Confident errors at t>=0.95: 1.2% in-family.
Shift warning (measured): in-family thresholds do not transfer — out-of-family
confident errors reached ~14% at t>=0.9. Use the runtime's per-workload
temperature fitting (POST /v1/calibrations, ~100 labeled examples) before
trusting thresholds on a new workload; it repaired scalar miscalibration to
3-4% confident errors in the repo's resampled experiment.
Use
git clone https://github.com/mpuig/system-one && cd system-one && uv sync
hf download mpuig/system-one-minicpm5-2b-q8 --local-dir system-one-minicpm5-2b-q8
uv run python scripts/serve.py --model system-one-minicpm5-2b-q8 \
--temperature system-one-minicpm5-2b-q8/temperature.json
Light 3-question request: ~195 ms p50 on an M4 Max. Apple Silicon required (MLX). Research prototype, not a certified production service; the honest failure record lives in the repo's decision log and experiments file.
- Downloads last month
- 129
8-bit
Model tree for mpuig/system-one-minicpm5-2b-q8
Base model
openbmb/MiniCPM5-2B-Base