MLEM now offers deployment to Kubernetes and Sagemaker with a single command.
Display all details about a specific MLEM Object from an existing MLEM project.
usage: mlem pprint [-p <path>] [--rev <commitish>] [-f]
[--json] [-h]
path
arguments:
path Path to objectAll MLEM objects can be printed to view their metadata. This includes generic
information such as requirements, type of object, hash, size, as well as object
specific information such as methods for a model or reader for data.
Since only one specific object is printed, a PATH to the specific MLEM object
is always required.
-p <path>, --project <path> - Path to MLEM project [default: (none)]--rev <commitish> - Repo revision to use [default: (none)]-f, --follow-links - If specified, follow the link to the actual object.--json - Output as json-h, --help - Show this message and exit.$ mlem pprint rf
⏳️ Loading meta from rf.mlem
{'artifacts': {'data': {'hash': 'a61a1fa54893dcebe6fa448df81a1418',
'size': 163651,
'type': 'dvc',
'uri': 'rf'}},
'model_type': {'methods': {'predict': {'args': [{'name': 'data',
'type_': {'columns': ['sepal '
'length '
'(cm)',
...$ mlem pprint https://github.com/iterative/example-mlem-get-started/iris.csv --rev 4-pack
⏳️ Loading meta from https://github.com/iterative/example-mlem-get-started/tree/4-pack/data/iris.csv.mlem
{'artifacts': {'data': {'hash': '45109f850511f9474665f2c26f4c79f3',
'size': 2470,
'uri': 'iris.csv'}},
'data_type': {'columns': ['sepal length (cm)',
'sepal width (cm)',
'petal length (cm)',
'petal width (cm)'],
'dtypes': ['float64', 'float64', 'float64', 'float64'],
'index_cols': [],
'type': 'dataframe'},
'object_type': 'data',
'reader': {'data_type': {'columns': ['sepal length (cm)',
'sepal width (cm)',
'petal length (cm)',
'petal width (cm)'],
'dtypes': ['float64',
'float64',
'float64',
'float64'],
'index_cols': [],
'type': 'dataframe'},
'format': 'csv',
'type': 'pandas'},
'requirements': [{'module': 'pandas', 'version': '1.4.2'}]}