Instructions to use twainsk/qev-230m-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use twainsk/qev-230m-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir qev-230m-mlx twainsk/qev-230m-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download NOTICE from twainsk/qev-230m-mlx: direct link, hf CLI and curl.
- Browser
- Download file 505 Bytes
-
https://huggingface.co/twainsk/qev-230m-mlx/resolve/main/NOTICE
- Command line
-
hf download hf://twainsk/qev-230m-mlx/NOTICE
-
curl -L -o NOTICE https://huggingface.co/twainsk/qev-230m-mlx/resolve/main/NOTICE
505 Bytes
| This model contains LiquidAI/LFM2.5-230M (revision 40cb2ad3b3044d5a41eee083a6103c8b523afa45) unchanged in backbone/, | |
| plus a decision LoRA adapter and pointer head trained by the Qev project | |
| (https://github.com/loadchange/qev). The adapter and pointer head are new files; the | |
| foundation weights were not modified. The whole directory is a Derivative Work distributed | |
| under the LFM Open License v1.0 (LICENSE). Commercial use by a Legal Entity with annual | |
| revenue of USD 10 million or more is not licensed. | |