Instructions to use pat883/attn-decode with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Kernels
How to use pat883/attn-decode with Kernels:
# !pip install kernels from kernels import get_kernel kernel = get_kernel("pat883/attn-decode") - Notebooks
- Google Colab
- Kaggle
metadata
library_name: kernels
tags:
- kernels
- rocm
Flash-Attention Decode (RDNA4/gfx1201)
Dense, paged, and fp8 flash-attention decode kernels (GQA, sliding-window, block-table KV cache).
Built with kernel-builder for AMD RDNA4 (gfx1201).
Load with the kernels library:
from kernels import get_kernel
kernel = get_kernel("pat883/attn-decode")
Requires a ROCm PyTorch build (torch 2.10 / ROCm 7.x) on an RDNA4 card. Built variants:
torch210-cxx11-rocm70andtorch210-cxx11-rocm71.