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Added zip-store help to README.md
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mreso committed Mar 28, 2023
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Expand Up @@ -56,10 +56,11 @@ torch-model-archiver --model-name densenet161 --version 1.0 --model-file example

```
$ torch-model-archiver -h
usage: torch-model-archiver [-h] --model-name MODEL_NAME --version MODEL_VERSION_NUMBER
--model-file MODEL_FILE_PATH --serialized-file MODEL_SERIALIZED_PATH
--handler HANDLER [--runtime {python,python3}]
[--export-path EXPORT_PATH] [-f] [--requirements-file]
usage: torch-model-archiver [-h] --model-name MODEL_NAME --handler HANDLER --version MODEL_VERSION_NUMBER
[--model-file MODEL_FILE_PATH] [--serialized-file MODEL_SERIALIZED_PATH]
[--runtime {python,python3}] [--export-path EXPORT_PATH]
[--archive-format {tgz,no-archive,zip-store,default}]
[-f] [--requirements-file]
Model Archiver Tool
Expand Down Expand Up @@ -93,7 +94,7 @@ optional arguments:
is an optional parameter. If --export-path is not
specified, the file will be saved in the current
working directory.
--archive-format {tgz,default}
--archive-format {tgz, no-archive, zip-store, default}
The format in which the model artifacts are archived.
"tgz": This creates the model-archive in <model-name>.tar.gz format.
If platform hosting requires model-artifacts to be in ".tar.gz"
Expand All @@ -102,6 +103,9 @@ optional arguments:
at "export-path/{model-name}" location. As a result of this choice,
MANIFEST file will be created at "export-path/{model-name}" location
without archiving these model files
"zip-store": This creates the model-archive in <model-name>.mar format
but will skip deflating the files to speed up creation. Mainly used
for testing purposes
"default": This creates the model-archive in <model-name>.mar format.
This is the default archiving format. Models archived in this format
will be readily hostable on TorchServe.
Expand Down Expand Up @@ -182,7 +186,7 @@ This will package all the model artifacts files and output `densenet_161.mar` in


### Model specific custom python requirements
Custom models/handlers may depend on different python packages which are not installed by-default as a part of `TorchServe` setup.
Custom models/handlers may depend on different python packages which are not installed by-default as a part of `TorchServe` setup.
Supply a [python requirements](https://pip.pypa.io/en/stable/user_guide/#requirements-files) file containing the list of required python packages to be installed by `TorchServe` for seamless model serving using `--requirements-file` parameter while creating the model-archiver.

Example:
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