Instructions to use baa-ai/MiniMax-M2.7-RAM-130GB-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use baa-ai/MiniMax-M2.7-RAM-130GB-MLX with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir MiniMax-M2.7-RAM-130GB-MLX baa-ai/MiniMax-M2.7-RAM-130GB-MLX
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Xet hash:
- 4eff36ec4bcd208e96536fe001b935f89121e64ed2c04f84f0ec60c0b39c7d52
- Size of remote file:
- 15.5 MB
- SHA256:
- 2b0639a138c0ccae63bce932b102cd4e1a344a9b7374cc3a9d42512592ddb52f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.