scikit-learn Model Type

Upload a scikit-learn Model to a Machine Learning Repository

Use the following function to upload a scikit-learn model to a Machine Learning repository in Artifactory:

import frogml

repository = "repository-name"
name = "model-name"
namespace = "namespace"
version = "version-1"
properties = {"key1": "value1"}
dependencies = ["path/to/dependencies/pyproject.toml", "path/to/dependencies/poetry.lock"]
code_dir = "full/path/to/code/dir"
joblib_model = get_scikit_learn() # Function that Returns a scikit learn model

frogml.scikit_learn.log_model(
    model=joblib_model,
    repository=repository,
    model_name=name,
    namespace=namespace,
    version=version,
    properties=properties,
    dependencies=dependencies,
    code_dir=code_dir,
)

Download a scikit-learn Model from a Machine Learning Repository

Use the following function to download a deserialized scikit-learn model from a Machine Learning repository in Artifactory:

import frogml

repository = "repository-name"
name = "model-name"
namespace = "namespace"
version = "version-1"
full_target_path = "full/path/to/target/path"

scikit_learn_deserialized_model = frogml.scikit_learn.load_model(
    repository=repository,
    namespace=namespace,
    model_name=name,
    version=version,
    target_path=full_target_path,
)

Get Information on a scikit-learn Model in a Machine Learning Repository

Use the following function to retrieve information on a specific scikit-learn model stored in a Machine Learning repository in Artifactory.

import frogml

repository = "repository-name"
name = "model-name"
namespace = "namespace"
version = "version-1"

frogml.scikit_learn.get_model_info(
    repository=repository,
    name=name,
    namespace=namespace,
    version=version,
)