Instructions to use pat883/gdn-hip with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Kernels
How to use pat883/gdn-hip with Kernels:
# !pip install kernels from kernels import get_kernel kernel = get_kernel("pat883/gdn-hip") - Notebooks
- Google Colab
- Kaggle
GDN-HIP (Gated Delta Net, RDNA4/gfx1201)
Native HIP + rocWMMA kernels for the Gated Delta Net linear-attention path: gdn_prefill/decode (+wmma/chunked), causal_conv1d, gated RMSNorm, with native backward + differentiable training wrappers.
Built with kernel-builder for AMD RDNA4 (gfx1201).
Load with the kernels library:
from kernels import get_kernel
kernel = get_kernel("pat883/gdn-hip")
Requires a ROCm PyTorch build (torch 2.10 / ROCm 7.x) on an RDNA4 card. Built variants:
torch210-cxx11-rocm70andtorch210-cxx11-rocm71.
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