Working with mixed adapter types

Normally, it is not possible to mix different adapter types in 🤗 PEFT. For example, even though it is possible to create a PEFT model that has two different LoRA adapters (that can have different config options), it is not possible to combine a LoRA adapter with a LoHa adapter. However, by using a mixed model, this works as long as the adapter types are compatible.

Loading different adapter types into a PEFT model

To load different adapter types into a PEFT model, proceed the same as if you were loading two adapters of the same type, but use PeftMixedModel instead of PeftModel:

from peft import PeftMixedModel

base_model = ...  # load the base model, e.g. from transformers
# load first adapter, which will be called "default"
peft_model = PeftMixedModel.from_pretrained(base_model, <path_to_adapter1>)
peft_model.load_adapter(<path_to_adapter2>, adapter_name="other")
peft_model.set_adapter(["default", "other"])

The last line is necessary if you want to activate both adapters, otherwise, only the first adapter would be active. Of course, you can add more different adapters by calling add_adapter repeatedly.

Currently, the main purpose of mixed adapter types is to combine trained adapters for inference. Although it is technically also possible to train a mixed adapter model, this has not been tested and is not recommended.

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