Model kinds

At the moment, we support the following kinds:

• model: represents a generic ML model
• mlflow: represents a MLflow model
• sklearn: represents a scikit-learn model
• huggingface: represents a HuggingFace model

For each different kind, the Model object has its own subclass with different spec and status attributes.

Model

The model kind indicates that the model is a generic ML model. It's usefull to represent a generic ML model as a Model object.

Model spec parameters

Parameter	Type	Description	Default
path	str	Path of the model, can be a local path or a remote path, a single filepath or a directory/partition.	required
framework	str	Model framework (e.g. 'pytorch').	None
algorithm	str	Model algorithm (e.g. 'resnet').	None
base_model	str	Base model.	None
parameters	dict	Model parameters.	None
metrics	dict	Model metrics.	None

Model methods

The model kind has no additional methods.

Mlflow

The mlflow kind indicates that the model is an MLflow model. It's usefull to represent an MLflow model as a Model object.

Mlflow spec parameters

Parameter	Type	Description	Default
path	str	Path of the model, can be a local path or a remote path, a single filepath or a directory/partition.	required
framework	str	Model framework (e.g. 'pytorch').	None
algorithm	str	Model algorithm (e.g. 'resnet').	None
base_model	str	Base model.	None
parameters	dict	Model parameters.	None
metrics	dict	Model metrics.	None
flavor	str	Mlflow model flavor.	None
model_config	dict	Mlflow model config.	None
input_datasets	list[Dataset]	Mlflow input datasets (see below).	None
signature	Signature	Mlflow model signature (see below).	None

Dataset

Parameter	Type	Description	Default
name	str	Dataset name.	None
digest	str	Dataset digest.	None
profile	str	Dataset profile.	None
schema	str	Dataset schema.	None
source	str	Dataset source.	None
source_type	str	Dataset source type.	None

Signature

Parameter	Type	Description	Default
inputs	str	Signature inputs.	None
outputs	str	Signature outputs.	None
parameters	str	Signature parameters.	None

Mlflow methods

The mlflow kind has no additional methods.

Sklearn

The sklearn kind indicates that the model is an Sklearn model. It's usefull to represent an Sklearn model as a Model object.

Sklearn spec parameters

Parameter	Type	Description	Default
path	str	Path of the model, can be a local path or a remote path, a single filepath or a directory/partition.	required
framework	str	Model framework (e.g. 'pytorch').	None
algorithm	str	Model algorithm (e.g. 'resnet').	None
base_model	str	Base model.	None
parameters	dict	Model parameters.	None
metrics	dict	Model metrics.	None

Sklearn methods

The sklearn kind has no additional methods.

Huggingface

The huggingface kind indicates that the model is an Huggingface model. It's usefull to represent an Huggingface model as a Model object.

Huggingface spec parameters

Parameter	Type	Description	Default
path	str	Path of the model, can be a local path or a remote path, a single filepath or a directory/partition.	required
framework	str	Model framework (e.g. 'pytorch').	None
algorithm	str	Model algorithm (e.g. 'resnet').	None
base_model	str	Base model.	None
parameters	dict	Model parameters.	None
metrics	dict	Model metrics.	None
model_id	str	Huggingface model id. If not specified, the model is loaded from the model path	None
model_revision	str	Huggingface model revision.	None

Huggingface methods

The huggingface kind has no additional methods.