Instructions to use KaedeTai/dflash2-mlx-quantized-draft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use KaedeTai/dflash2-mlx-quantized-draft with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download KaedeTai/dflash2-mlx-quantized-draft --local-dir dflash2-mlx-quantized-draft
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Commit History
-
fix: M5 Max is 128 GB, not 137 GB (byte-count/1e9 conversion error)
Verified signaturee3c1203 -
fix: 16.1 GB resident (measured), not 15.5 GB of disk weights
Verified signature97877d3 -
DFlash2 quantized-draft loader + M5 Max measurements
Verified signature78c877d -
initial commit
Verified signature2589942