Instructions to use replicate/deep-gemm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Kernels
How to use replicate/deep-gemm with Kernels:
# !pip install kernels from kernels import get_kernel # a version (or an explicit revision) is required; see the "Files and versions" tab for the available ones kernel = get_kernel("replicate/deep-gemm", version=1) - Notebooks
- Google Colab
- Kaggle
Build uploaded using `kernels` (batch 1/10).
Browse files- .gitattributes +1 -0
- build/torch210-cxx11-cu126-x86_64-linux/{_deep_gemm_cuda_5c4fc0a.abi3.so → _deep_gemm_cuda_a68a39f.abi3.so} +1 -1
- build/torch210-cxx11-cu126-x86_64-linux/_ops.py +3 -3
- build/torch210-cxx11-cu128-x86_64-linux/_deep_gemm_cuda_5c4fc0a.abi3.so +0 -3
- build/torch210-cxx11-cu130-x86_64-linux/_deep_gemm_cuda_5c4fc0a.abi3.so +0 -3
- build/torch29-cxx11-cu126-x86_64-linux/_deep_gemm_cuda_5c4fc0a.abi3.so +0 -3
- build/torch29-cxx11-cu128-x86_64-linux/_deep_gemm_cuda_5c4fc0a.abi3.so +0 -3
- build/torch29-cxx11-cu130-x86_64-linux/_deep_gemm_cuda_5c4fc0a.abi3.so +0 -3
.gitattributes
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ops = torch.ops._deep_gemm_cuda_a68a39f
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