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Python class

ModelArtifact

ModelArtifact

class max.pipelines.lib.artifact.ModelArtifact(model=None, tokenizer=None, format_spec=None, engine_config=None, kv_cache=None, batch_processor=None, weight_loader=None)

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Bases: object

Serializable serve-able pipeline.

Parameters:

• model (ArtifactComponent | None)
• tokenizer (ArtifactComponent | None)
• format_spec (ArtifactComponent | None)
• engine_config (ArtifactComponent | None)
• kv_cache (ArtifactComponent | None)
• batch_processor (ArtifactComponent | None)
• weight_loader (ArtifactComponent | None)

batch_processor

batch_processor: ArtifactComponent | None = None

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component_slots()

classmethod component_slots()

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Returns the names of the component slots.

Return type:

tuple[str, …]

component_types()

classmethod component_types()

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Returns the class each slot is deserialized with.

Returns:

A mapping from slot name to component class, or to None for a slot still annotated with the ArtifactComponent protocol.

Raises:

ArtifactError – If a slot’s annotation names more than one class or a class that isn’t an ArtifactComponent.

Return type:

dict[str, type[ArtifactComponent] | None]

components()

components()

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Returns the set component slots, keyed by slot name.

Return type:

dict[str, ArtifactComponent]

engine_config

engine_config: ArtifactComponent | None = None

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format_spec

format_spec: ArtifactComponent | None = None

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kv_cache

kv_cache: ArtifactComponent | None = None

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model

model: ArtifactComponent | None = None

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model_sources()

model_sources()

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Returns the unique Hugging Face references in the components.

Serializes every component, so prefer reading ArtifactMetadata.model_sources from an exported artifact.

Return type:

tuple[HuggingFaceRef, …]

tokenizer

tokenizer: ArtifactComponent | None = None

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weight_loader

weight_loader: ArtifactComponent | None = None

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