def _load_pipeline_instance()

in docker_images/adapter_transformers/app/pipelines/base.py [0:0]

• 13 lines of code
• 2 McCabe index (conditional complexity)

    def _load_pipeline_instance(pipeline_class, adapter_id):
        adapter_info = get_adapter_info(adapter_id, source="hf")
        if adapter_info is None:
            raise ValueError(f"Adapter with id '{adapter_id}' not available.")

        tokenizer = AutoTokenizer.from_pretrained(adapter_info.model_name)
        model = AutoAdapterModel.from_pretrained(adapter_info.model_name)
        model.load_adapter(adapter_id, source="hf", set_active=True)

        # Transformers incorrectly logs an error because class name is not known. Filter this out.
        logger.addFilter(
            lambda record: not record.getMessage().startswith(
                f"The model '{model.__class__.__name__}' is not supported"
            )
        )

        return pipeline_class(model=model, tokenizer=tokenizer)