Instructions to use usermma/NEXUS-Coder-Abliterated-mlx-fp16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use usermma/NEXUS-Coder-Abliterated-mlx-fp16 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir NEXUS-Coder-Abliterated-mlx-fp16 usermma/NEXUS-Coder-Abliterated-mlx-fp16
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
- Xet hash:
- 55cb41a60a394602f01a48fe5eb99f078a3fe1882b3c4b089558481b64c6c0bd
- Size of remote file:
- 3.09 GB
- SHA256:
- 7ec9f976ac571127322298cee05995e21d0648d4ef6bcfcb083ab2a94d31874e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.