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Added Triton deployment instructions to documentation #1116
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@narendasan can we have this merged before EoW? This is needed for marketing release. |
Changing reviewer to @peri044 |
# <xx.xx> is the yy:mm for the publishing tag for NVIDIA's Pytorch | ||
# container; eg. 22.04 | ||
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docker run -it --gpus all -v /path/to/folder:/resnet50_eg nvcr.io/nvidia/pytorch:<xx.xx>-py3 |
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-v /path/to/folder:/resnet50_eg
- is this required here ?
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If so, please elaborate in the README as to which folder we should mount to docker
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path/to/local/folder/to/copy/model:/resnet50_eg
is this required here ?
Like torch.hub will automatically download the RN50 model right as per model = torch.hub.load('pytorch/vision:v0.10.0', 'resnet50', pretrained=True).eval().to("cuda")
?
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Also, resnet50_eg
it is not being used anywhere in the instructions. We don't need this I think
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Is this resolved ?
Description
Added documentation about deploying a model to triton
Fixes # (issue)
Type of change
Please delete options that are not relevant and/or add your own.