Instructions to use nsalerni/loudink-v1.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use nsalerni/loudink-v1.5 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir loudink-v1.5 nsalerni/loudink-v1.5
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
- Xet hash:
- 87c02d8f3024b70a644c2b95f64fa59f4bb1e9d62c9242dfecdaa336079c70bb
- Size of remote file:
- 44.5 MB
- SHA256:
- ceb709ccf7a40ea608c5cc74c247071bbcb0980017f1811f7c55604b4241ab7c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.