Instructions to use mlx-community/clef-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/clef-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download mlx-community/clef-4bit --local-dir clef-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Add Typed Decisions benchmark results
Browse filesAdds this model's scores on [Typed Decisions](https://huggingface.co/datasets/LocalLLaMA/typed-decisions) as `.eval_results/typed-decisions.yaml`, so they are listed on the benchmark's Hub leaderboard.
| Accuracy | KL from gold (lower is better) | Brier (lower is better) | ECE (lower is better) |
|---|---|---|---|
| 0.7185 | 0.1987 | 0.106 | 0.1185 |
General model (any question schema at request time), not fitted by us on this benchmark's train split. Scored on the full 400-case test split (2,000 decisions): one request per case with all five questions, text only, the benchmark's own metrics, MLX on an Apple M3 Max.
Once merged, the model appears on the leaderboard. Quantizations and other derived models are hidden by default; turn the base-model switch off to see them. While this PR is open the Hub marks the scores as community-provided.
If you would rather not list the model, or a number looks wrong, close this PR or tell us and we will correct it. Scored by codelion (OptiQ).
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- dataset:
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id: LocalLLaMA/typed-decisions
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task_id: accuracy
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value: 0.7185
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source:
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url: https://huggingface.co/datasets/LocalLLaMA/typed-decisions
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name: Typed Decisions leaderboard (README)
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user: LocalLLaMA
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notes: "General model (any question schema at request time), not fitted by us on this benchmark's train split. Scored on the full 400-case test split (2,000 decisions): one request per case with all five questions, text only, the benchmark's own metrics, MLX on an Apple M3 Max."
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- dataset:
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id: LocalLLaMA/typed-decisions
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task_id: kl_from_gold
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value: 0.1987
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source:
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url: https://huggingface.co/datasets/LocalLLaMA/typed-decisions
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name: Typed Decisions leaderboard (README)
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user: LocalLLaMA
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notes: "General model (any question schema at request time), not fitted by us on this benchmark's train split. Scored on the full 400-case test split (2,000 decisions): one request per case with all five questions, text only, the benchmark's own metrics, MLX on an Apple M3 Max."
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- dataset:
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id: LocalLLaMA/typed-decisions
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task_id: brier
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value: 0.106
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source:
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url: https://huggingface.co/datasets/LocalLLaMA/typed-decisions
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name: Typed Decisions leaderboard (README)
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user: LocalLLaMA
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notes: "General model (any question schema at request time), not fitted by us on this benchmark's train split. Scored on the full 400-case test split (2,000 decisions): one request per case with all five questions, text only, the benchmark's own metrics, MLX on an Apple M3 Max."
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- dataset:
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id: LocalLLaMA/typed-decisions
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task_id: ece
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value: 0.1185
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source:
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url: https://huggingface.co/datasets/LocalLLaMA/typed-decisions
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name: Typed Decisions leaderboard (README)
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user: LocalLLaMA
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notes: "General model (any question schema at request time), not fitted by us on this benchmark's train split. Scored on the full 400-case test split (2,000 decisions): one request per case with all five questions, text only, the benchmark's own metrics, MLX on an Apple M3 Max."
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