Instructions to use killen8/Nanbeige4.3-33B-MLX-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use killen8/Nanbeige4.3-33B-MLX-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download killen8/Nanbeige4.3-33B-MLX-4bit --local-dir Nanbeige4.3-33B-MLX-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Nanbeige4.3-33B-MLX-4bit
4-bit (group size 64, ~4.5 bits/weight) MLX conversion of Nanbeige/Nanbeige4.3-33B, sized for 32-48 GB Apple Silicon Macs.
Measured on an M4 Pro, 48 GB (mlx-lm 0.29.1):
| Disk | 17 GB |
| Peak memory | 18.8 GB |
| Generation | ~13.7 tok/s |
Usage:
pip install mlx-lm
mlx_lm generate --model <this-repo> --prompt "Hello" --temp 0.6 --top-p 0.95
Recommended settings follow the original card (agentic: temp 1.0, top_p 0.95; chat/reasoning: temp 0.6, top_p 0.95). The model thinks by default; enable_thinking=False turns it off.
Quantized with a streaming shard-by-shard script (all 2-D linear and embedding weights to 4-bit, norms in bf16). Quality was spot-checked only; benchmarks are those of the original model, not re-run on this quant. License is Apache 2.0, inherited from the base model.
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Model size
33B params
Tensor type
U32
·
BF16 ·
Hardware compatibility
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4-bit
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