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vllm.model_executor.models.transformers

Wrapper around transformers models

Modules:

Name Description
base

Transformers backend base class.
causal

Transformers backend mixin for causal language models.
legacy

Transformers backend mixin for legacy models.
moe

Transformers backend mixin for Mixture of Experts (MoE) models.
multimodal

Transformers backend mixin for multi-modal models.
pooling

Transformers backend mixins for pooling models.
utils

Transformers backend utilities.

TransformersEmbeddingModel

Bases: EmbeddingMixin, LegacyMixin, Base

Source code in vllm/model_executor/models/transformers/__init__.py 
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@support_torch_compile(enable_if=can_enable_torch_compile)
class TransformersEmbeddingModel(EmbeddingMixin, LegacyMixin, Base): ...

TransformersForCausalLM

Bases: CausalMixin, Base

Source code in vllm/model_executor/models/transformers/__init__.py 
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@support_torch_compile(enable_if=can_enable_torch_compile)
class TransformersForCausalLM(CausalMixin, Base): ...

TransformersForSequenceClassification

Bases: SequenceClassificationMixin, LegacyMixin, Base

Source code in vllm/model_executor/models/transformers/__init__.py 
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@support_torch_compile(enable_if=can_enable_torch_compile)
class TransformersForSequenceClassification(
    SequenceClassificationMixin, LegacyMixin, Base
): ...

TransformersMoEEmbeddingModel

Bases: EmbeddingMixin, MoEMixin, Base

Source code in vllm/model_executor/models/transformers/__init__.py 
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@support_torch_compile(enable_if=can_enable_torch_compile)
class TransformersMoEEmbeddingModel(EmbeddingMixin, MoEMixin, Base): ...

TransformersMoEForCausalLM

Bases: MoEMixin, CausalMixin, Base

Source code in vllm/model_executor/models/transformers/__init__.py 
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@support_torch_compile(enable_if=can_enable_torch_compile)
class TransformersMoEForCausalLM(MoEMixin, CausalMixin, Base): ...

TransformersMoEForSequenceClassification

Bases: SequenceClassificationMixin, MoEMixin, Base

Source code in vllm/model_executor/models/transformers/__init__.py 
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@support_torch_compile(enable_if=can_enable_torch_compile)
class TransformersMoEForSequenceClassification(
    SequenceClassificationMixin, MoEMixin, Base
): ...

TransformersMultiModalEmbeddingModel

Bases: EmbeddingMixin, MultiModalMixin, Base

Source code in vllm/model_executor/models/transformers/__init__.py 
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@MULTIMODAL_REGISTRY.register_processor(
    MultiModalProcessor,
    info=MultiModalProcessingInfo,
    dummy_inputs=MultiModalDummyInputsBuilder,
)
@support_torch_compile(
    dynamic_arg_dims=DYNAMIC_ARG_DIMS, enable_if=can_enable_torch_compile
)
class TransformersMultiModalEmbeddingModel(EmbeddingMixin, MultiModalMixin, Base): ...

TransformersMultiModalForCausalLM

Bases: MultiModalMixin, CausalMixin, Base

Source code in vllm/model_executor/models/transformers/__init__.py 
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@MULTIMODAL_REGISTRY.register_processor(
    MultiModalProcessor,
    info=MultiModalProcessingInfo,
    dummy_inputs=MultiModalDummyInputsBuilder,
)
@support_torch_compile(
    dynamic_arg_dims=DYNAMIC_ARG_DIMS, enable_if=can_enable_torch_compile
)
class TransformersMultiModalForCausalLM(MultiModalMixin, CausalMixin, Base): ...

TransformersMultiModalForSequenceClassification

Bases: SequenceClassificationMixin, MultiModalMixin, Base

Source code in vllm/model_executor/models/transformers/__init__.py 
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@MULTIMODAL_REGISTRY.register_processor(
    MultiModalProcessor,
    info=MultiModalProcessingInfo,
    dummy_inputs=MultiModalDummyInputsBuilder,
)
@support_torch_compile(
    dynamic_arg_dims=DYNAMIC_ARG_DIMS, enable_if=can_enable_torch_compile
)
class TransformersMultiModalForSequenceClassification(
    SequenceClassificationMixin, MultiModalMixin, Base
): ...

TransformersMultiModalMoEForCausalLM

Bases: MoEMixin, MultiModalMixin, CausalMixin, Base

Source code in vllm/model_executor/models/transformers/__init__.py 
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@MULTIMODAL_REGISTRY.register_processor(
    MultiModalProcessor,
    info=MultiModalProcessingInfo,
    dummy_inputs=MultiModalDummyInputsBuilder,
)
@support_torch_compile(
    dynamic_arg_dims=DYNAMIC_ARG_DIMS, enable_if=can_enable_torch_compile
)
class TransformersMultiModalMoEForCausalLM(
    MoEMixin, MultiModalMixin, CausalMixin, Base
): ...

__getattr__ 

__getattr__(name: str)

Handle imports of non-existent classes with a helpful error message.

Source code in vllm/model_executor/models/transformers/__init__.py 
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def __getattr__(name: str):
    """Handle imports of non-existent classes with a helpful error message."""
    if name not in globals():
        raise AttributeError(
            "The Transformers backend does not currently have a class to handle "
            f"the requested model type: {name}. Please open an issue at "
            "https://github.com/vllm-project/vllm/issues/new"
        )
    return globals()[name]