Instructions to use Efficient-Large-Model/Sol-Attn-Kernel-Source with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Kernels
How to use Efficient-Large-Model/Sol-Attn-Kernel-Source with Kernels:
# !pip install kernels from kernels import get_kernel kernel = get_kernel("Efficient-Large-Model/Sol-Attn-Kernel-Source") - Notebooks
- Google Colab
- Kaggle
| # Source provenance | |
| - Upstream repository: <https://github.com/NVlabs/Sana> | |
| - Upstream branch: `sol-engine` | |
| - Upstream commit: `8a26fb0ec9e353125ead798cb2e312d5ce48cded` | |
| - Upstream path: `techniques/sparse_backends/sol_attn` | |
| - Kernel Hub target: `Efficient-Large-Model/Sol-Attn` | |
| `torch-ext/sol_attn` contains the complete upstream package at the pinned | |
| commit. Its only packaging-level changes are semantically equivalent | |
| absolute-to-relative internal imports. Kernel Hub loads each kernel version | |
| under an isolated module name, so hard-coded `sol_attn.*` package imports | |
| would otherwise escape that namespace. | |
| Given a checkout of the pinned Sana commit, verify the file inventory, all | |
| non-import source text, and import semantics with: | |
| ```bash | |
| python tools/verify_upstream.py /path/to/Sana | |
| ``` | |
| The publishing process does not add files, workflows, or commits to | |
| `NVlabs/Sana`. | |