Instructions to use WEO-SAS/mamba-ssm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Kernels
How to use WEO-SAS/mamba-ssm with Kernels:
# !pip install kernels from kernels import get_kernel kernel = get_kernel("WEO-SAS/mamba-ssm") - Notebooks
- Google Colab
- Kaggle
This is a compiled CUDA kernel package, not a model. It provides the Mamba selective-scan operation (selective_scan_fn, Mamba, Mamba2, etc.) for use with the Hugging Face kernels library. WEO-SAS built it to support the mamba-* variants of sen2sr, which need a compiled selective-scan kernel for their Mamba/Swin2SR backbone. This is an internal/experimental build — it has not been validated for production use.
This is the repository card of kernels-community/mamba-ssm that has been pushed on the Hub. It was built to be used with the kernels library. This card was automatically generated.
How to use
# make sure `kernels` is installed: `pip install -U kernels`
from kernels import get_kernel
kernel_module = get_kernel("WEO-SAS/mamba-ssm")
selective_scan_fn = kernel_module.selective_scan_fn
selective_scan_fn(...)
Available functions
selective_scan_fnmamba_inner_fnfalcon_mamba_inner_fnselective_state_updatemamba_chunk_scan_combinedmamba_split_conv1d_scan_combinedMambaMamba2MambaLMHeadModel
Benchmarks
No benchmark available yet.
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