Instructions to use baa-ai/Llama-3.3-70B-Instruct-RAM-50GB-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use baa-ai/Llama-3.3-70B-Instruct-RAM-50GB-MLX with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Llama-3.3-70B-Instruct-RAM-50GB-MLX baa-ai/Llama-3.3-70B-Instruct-RAM-50GB-MLX
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
- Xet hash:
- a326990dd152b510479e6173d6d74b50aba7823a50aea8a151b3cbf849c4a3d6
- Size of remote file:
- 2.1 GB
- SHA256:
- 7a0049d6a5e14ea8491a9d67aba63f6647ddc434292ab9d2a1ab3d7474c35adb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.