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def get_model(model_name, adapted_component, adaptor_class, num_steers, rank,
epsilon, init_var, low_resource_mode):
if model_name.startswith("EleutherAI/gpt-neo") or \
model_name.startswith("gpt2"):
from lm_steer.models.model_gpt_neo import Switching_GPTNeoModel
model = Switching_GPTNeoModel(
model_name, adapted_component, adaptor_class, num_steers, rank,
epsilon, init_var, low_resource_mode)
return model, model.tokenizer
elif model_name.startswith("lora-gpt2"):
from lm_steer.models.model_lora_gpt_neo import LORA_GPTNeoModel
model = LORA_GPTNeoModel(model_name, rank, epsilon)
return model, model.tokenizer
elif model_name.startswith("embedding_tuning"):
from lm_steer.models.model_embedding_tuning_gpt_neo import \
EmbeddingTuning_GPTNeoModel
model = EmbeddingTuning_GPTNeoModel(model_name)
return model, model.tokenizer
elif model_name.startswith("prefix-gpt2"):
from lm_steer.models.model_prefix_gpt_neo import PREFIX_GPTNeoModel
model = PREFIX_GPTNeoModel(model_name)
return model, model.tokenizer
elif model_name.startswith("EleutherAI/pythia"):
from lm_steer.models.model_gpt_neox import Switching_GPTNeoXModel
model = Switching_GPTNeoXModel(
model_name, adapted_component, adaptor_class, num_steers, rank,
epsilon, init_var, low_resource_mode)
return model, model.tokenizer
elif model_name.startswith("EleutherAI/gpt-j"):
from lm_steer.models.model_gpt_j import Switching_GPTJModel
model = Switching_GPTJModel(
model_name, adapted_component, adaptor_class, num_steers, rank,
epsilon, init_var, low_resource_mode)
return model, model.tokenizer
elif model_name.startswith("microsoft/DialoGPT"):
from lm_steer.models.model_dialogpt import Switching_DialoGPTModel
model = Switching_DialoGPTModel(
model_name, adapted_component, adaptor_class, num_steers, rank,
epsilon, init_var, low_resource_mode)
return model, model.tokenizer
else:
raise NotImplementedError()
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