Instructions to use GreenBitAI/Mistral-7B-Instruct-v0.2-layer-mix-bpw-2.2-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use GreenBitAI/Mistral-7B-Instruct-v0.2-layer-mix-bpw-2.2-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Mistral-7B-Instruct-v0.2-layer-mix-bpw-2.2-mlx GreenBitAI/Mistral-7B-Instruct-v0.2-layer-mix-bpw-2.2-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
GreenBitAI/Mistral-7B-Instruct-v0.2-layer-mix-bpw-2.2-mlx
This quantized low-bit model was converted to MLX format from GreenBitAI/Mistral-7B-Instruct-v0.2-layer-mix-bpw-2.2.
Refer to the original model card for more details on the model.
Use with mlx
pip install gbx-lm
from gbx_lm import load, generate
model, tokenizer = load("GreenBitAI/Mistral-7B-Instruct-v0.2-layer-mix-bpw-2.2-mlx")
response = generate(model, tokenizer, prompt="hello", verbose=True)
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Model size
0.9B params
Tensor type
F16
路
I16 路
U32 路
Hardware compatibility
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Quantized
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