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27 lines
1.1 KiB
Python
27 lines
1.1 KiB
Python
from pathlib import Path
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from typing import Optional
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from transformers import SiglipVisionModel
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from invokeai.backend.model_manager.configs.factory import AnyModelConfig
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from invokeai.backend.model_manager.load.load_default import ModelLoader
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from invokeai.backend.model_manager.load.model_loader_registry import ModelLoaderRegistry
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from invokeai.backend.model_manager.taxonomy import AnyModel, BaseModelType, ModelFormat, ModelType, SubModelType
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@ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.SigLIP, format=ModelFormat.Diffusers)
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class SigLIPModelLoader(ModelLoader):
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"""Class for loading SigLIP models."""
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def _load_model(
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self,
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config: AnyModelConfig,
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submodel_type: Optional[SubModelType] = None,
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) -> AnyModel:
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if submodel_type is not None:
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raise ValueError("Unexpected submodel requested for LLaVA OneVision model.")
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model_path = Path(config.path)
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model = SiglipVisionModel.from_pretrained(model_path, local_files_only=True, torch_dtype=self._torch_dtype)
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return model
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