Instructions to use Neo39982/Behemoth-R1-123B-v2-mlx-4Bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use Neo39982/Behemoth-R1-123B-v2-mlx-4Bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Behemoth-R1-123B-v2-mlx-4Bit Neo39982/Behemoth-R1-123B-v2-mlx-4Bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download model-00001-of-00014.safetensors from Neo39982/Behemoth-R1-123B-v2-mlx-4Bit: direct link, hf CLI and curl.
- Browser
- Download file 5.28 GB
-
https://huggingface.co/Neo39982/Behemoth-R1-123B-v2-mlx-4Bit/resolve/main/model-00001-of-00014.safetensors
- Command line
-
hf download hf://Neo39982/Behemoth-R1-123B-v2-mlx-4Bit/model-00001-of-00014.safetensors
-
curl -L -o model-00001-of-00014.safetensors https://huggingface.co/Neo39982/Behemoth-R1-123B-v2-mlx-4Bit/resolve/main/model-00001-of-00014.safetensors
5.28 GB
- Xet hash:
- bef8114f7be867372386bf44b4c85d93ea65a26b7c0796cd511744d3ecc323e7
- Size of remote file:
- 5.28 GB
- SHA256:
- dc0183097eefae83012a31041b6a2a185d4dca51323511f1720abe2c43396305
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.