Instructions to use kernels-staging/msa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Kernels
How to use kernels-staging/msa with Kernels:
# !pip install kernels from kernels import get_kernel kernel = get_kernel("kernels-staging/msa") - Notebooks
- Google Colab
- Kaggle
This is the repository card of kernels-community/msa 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("kernels-community/msa", version=0)
sparse_atten_func = kernel_module.sparse_atten_func
sparse_atten_func(...)
Available functions
sparse_atten_funcsparse_atten_nvfp4_kv_funcsparse_decode_atten_funcSparseDecodePagedAttentionWrapperfp4_indexer_block_scoresbuild_k2q_csrSparseK2qCsrBuilderSm100Nvfp4QuantizedTensorquantize_bf16_to_nvfp4_128x4quantize_kv_bf16_to_nvfp4_128x4dequantize_nvfp4_128x4_to_bf16swizzle_nvfp4_scale_to_128x4nvfp4_global_scale_from_amax
Benchmarks
No benchmark available yet.
Source code
Source code of this kernel originally comes from https://github.com/MiniMax-AI/MSA and it was repurposed for compatibility with kernels.
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