Instructions to use dicksondickson/VeriLoop-E2-oQ5e-mtp-bf16-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use dicksondickson/VeriLoop-E2-oQ5e-mtp-bf16-MLX with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download dicksondickson/VeriLoop-E2-oQ5e-mtp-bf16-MLX --local-dir VeriLoop-E2-oQ5e-mtp-bf16-MLX
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
dicksondickson/VeriLoop-E2-oQ5e-mtp-bf16-MLX
This model is a quantization of: https://huggingface.co/tsinghua-sigs-robot-lab/VeriLoop-E2
This checkpoint was quantized using oMLX 0.7.0 with imatrix enabled.
Important tensors are left at bf16 which is for Apple M3 chips and later.
Run the model using oMLX: https://github.com/jundot/omlx
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Model size
28B params
Tensor type
U32
·
BF16 ·
U8 ·
I8 ·
I16 ·
I64 ·
I32 ·
Hardware compatibility
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5-bit
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