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Huggingface

Initialization of the Huggingface integration.

HuggingfaceIntegration

Bases: Integration

Definition of Huggingface integration for ZenML.

Source code in src/zenml/integrations/huggingface/__init__.py 
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class HuggingfaceIntegration(Integration):
    """Definition of Huggingface integration for ZenML."""

    NAME = HUGGINGFACE

    REQUIREMENTS_IGNORED_ON_UNINSTALL = ["fsspec", "pandas"]

    @classmethod
    def activate(cls) -> None:
        """Activates the integration."""
        from zenml.integrations.huggingface import materializers  # noqa
        from zenml.integrations.huggingface import services

    @classmethod
    def get_requirements(cls, target_os: Optional[str] = None) -> List[str]:
        """Defines platform specific requirements for the integration.

        Args:
            target_os: The target operating system.

        Returns:
            A list of requirements.
        """
        requirements = [
            "datasets>=2.16.0",
            "huggingface_hub>0.19.0",
            "accelerate",
            "bitsandbytes>=0.41.3",
            "peft",
            "transformers",
        ]

        # Add the pandas integration requirements
        from zenml.integrations.pandas import PandasIntegration

        return requirements + \
            PandasIntegration.get_requirements(target_os=target_os)

    @classmethod
    def flavors(cls) -> List[Type[Flavor]]:
        """Declare the stack component flavors for the Huggingface integration.

        Returns:
            List of stack component flavors for this integration.
        """
        from zenml.integrations.huggingface.flavors import (
            HuggingFaceModelDeployerFlavor,
        )

        return [HuggingFaceModelDeployerFlavor]

activate() classmethod

Activates the integration.

Source code in src/zenml/integrations/huggingface/__init__.py 
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@classmethod
def activate(cls) -> None:
    """Activates the integration."""
    from zenml.integrations.huggingface import materializers  # noqa
    from zenml.integrations.huggingface import services

flavors() classmethod

Declare the stack component flavors for the Huggingface integration.

Returns:

Type Description
List[Type[Flavor]]

List of stack component flavors for this integration.
Source code in src/zenml/integrations/huggingface/__init__.py 
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@classmethod
def flavors(cls) -> List[Type[Flavor]]:
    """Declare the stack component flavors for the Huggingface integration.

    Returns:
        List of stack component flavors for this integration.
    """
    from zenml.integrations.huggingface.flavors import (
        HuggingFaceModelDeployerFlavor,
    )

    return [HuggingFaceModelDeployerFlavor]

get_requirements(target_os=None) classmethod

Defines platform specific requirements for the integration.

Parameters:

Name Type Description Default
target_os Optional[str]

The target operating system.

 None

Returns:

Type Description
List[str]

A list of requirements.
Source code in src/zenml/integrations/huggingface/__init__.py 
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@classmethod
def get_requirements(cls, target_os: Optional[str] = None) -> List[str]:
    """Defines platform specific requirements for the integration.

    Args:
        target_os: The target operating system.

    Returns:
        A list of requirements.
    """
    requirements = [
        "datasets>=2.16.0",
        "huggingface_hub>0.19.0",
        "accelerate",
        "bitsandbytes>=0.41.3",
        "peft",
        "transformers",
    ]

    # Add the pandas integration requirements
    from zenml.integrations.pandas import PandasIntegration

    return requirements + \
        PandasIntegration.get_requirements(target_os=target_os)