Instructions to use rynky2436/Llama-3.2-8X3B-MOE-istruct-uncensored-abliterated-18.4B-mlx-oQ8-fp16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use rynky2436/Llama-3.2-8X3B-MOE-istruct-uncensored-abliterated-18.4B-mlx-oQ8-fp16 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Llama-3.2-8X3B-MOE-istruct-uncensored-abliterated-18.4B-mlx-oQ8-fp16 rynky2436/Llama-3.2-8X3B-MOE-istruct-uncensored-abliterated-18.4B-mlx-oQ8-fp16
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
Llama-3.2-8X3B-MOE-Dark-Champion-Instruct-uncensored-abliterated-18.4B-mlx-oQ8-fp16
This model was quantized using oQ (oMLX v0.3.9.dev2) mixed-precision quantization.
Quantization details
- Model type: mixtral
- Bits: 8
- Group size: 64
- Format: MLX safetensors
- Downloads last month
- 663
Model size
5B params
Tensor type
F16
·
U32 ·
Hardware compatibility
Log In to add your hardware
8-bit
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support