Instructions to use replicate/relu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Kernels
How to use replicate/relu 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/relu", version=1) - Notebooks
- Google Colab
- Kaggle
Uploaded using `kernel-builder`.
Browse files
.gitattributes
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@@ -360,3 +360,4 @@ build/torch29-cxx11-cu129-aarch64-linux/_relu_cuda_918d6dc.abi3.so filter=lfs di
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build/torch210-xpu20253-x86_64-windows/_relu_xpu_e08ad6f.pyd filter=lfs diff=lfs merge=lfs -text
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build/torch211-cu128-x86_64-windows/_relu_cuda_f560032.pyd filter=lfs diff=lfs merge=lfs -text
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build/torch210-xpu20253-x86_64-windows/_relu_xpu_f560032.pyd filter=lfs diff=lfs merge=lfs -text
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build/torch210-xpu20253-x86_64-windows/_relu_xpu_e08ad6f.pyd filter=lfs diff=lfs merge=lfs -text
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build/torch211-cu128-x86_64-windows/_relu_cuda_f560032.pyd filter=lfs diff=lfs merge=lfs -text
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build/torch210-xpu20253-x86_64-windows/_relu_xpu_f560032.pyd filter=lfs diff=lfs merge=lfs -text
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build/torch211-cu128-x86_64-windows/_relu_cuda_e46713e.pyd filter=lfs diff=lfs merge=lfs -text
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build/torch211-cu128-x86_64-windows/_ops.py
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import torch
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from . import
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ops = torch.ops.
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def add_op_namespace_prefix(op_name: str):
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"""
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Prefix op by namespace.
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"""
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return f"
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import torch
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from . import _relu_cuda_e46713e
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ops = torch.ops._relu_cuda_e46713e
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def add_op_namespace_prefix(op_name: str):
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"""
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Prefix op by namespace.
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"""
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return f"_relu_cuda_e46713e::{op_name}"
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build/torch211-cu128-x86_64-windows/{_relu_cuda_f560032.pyd → _relu_cuda_e46713e.pyd}
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 203776
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version https://git-lfs.github.com/spec/v1
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oid sha256:95eb57b01f8c3d815a7e4a71e9ae83856f3f6e97d49cdf0b969b0797e3979792
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size 203776
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