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Create a .mlem
metafile for a model or data in any file or directory.
usage: mlem import [options] uri target
arguments:
URI File to import [required]
TARGET Path to save MLEM object [required]
Use import
on an existing data or model files (or directories) to generate the
necessary .mlem
metafiles for them. This is useful to quickly make existing
data and model files compatible with MLEM, which then can be used in future
operations such as mlem apply
.
This command provides a quick and easy alternative to writing python code to load those models/datasets into object for subsequent usage in MLEM context.
-p, --project TEXT
: Path to MLEM project [default: (none)]--rev TEXT
: Repo revision to use [default: (none)]--target-project, --tp TEXT
: Project to save target to [default: (none)]--copy / --no-copy
: Whether to create a copy of file in target location or
just link existing file [default: copy]--type TEXT
: Specify how to read file Available types: ['pandas', 'pickle']
[default: (auto infer)]--index / --no-index
: Whether to index output in .mlem directory-e, --external
: Save result not in .mlem, but directly in project-h, --help
: Show this message and exit.Create a MLEM dataset from a local .csv
file
$ mlem import data/data.csv data/imported_data --type pandas[csv]
...
Create a MLEM model from local .pkl
(pickle) file
$ mlem import data/model.pkl data/imported_model
...
Create a MLEM model from remote .pkl
(pickle) file
$ mlem import .mlem/model/rf --project https://github.com/iterative/example-mlem-get-started --rev simple data/imported_model --type pickle
💾 Saving model to .mlem/model/data/imported_model.mlem