| # Copyright 2024 the LlamaFactory team. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| from typing import TYPE_CHECKING | |
| from ...extras.constants import MOD_SUPPORTED_MODELS | |
| if TYPE_CHECKING: | |
| from transformers import PretrainedConfig, PreTrainedModel | |
| from ...hparams import ModelArguments | |
| def load_mod_pretrained_model(**init_kwargs) -> "PreTrainedModel": | |
| from MoD import AutoMoDModelForCausalLM | |
| return AutoMoDModelForCausalLM.from_pretrained(**init_kwargs) | |
| def convert_pretrained_model_to_mod( | |
| model: "PreTrainedModel", config: "PretrainedConfig", model_args: "ModelArguments" | |
| ) -> "PreTrainedModel": | |
| from MoD import apply_mod_to_hf | |
| if getattr(config, "model_type", None) not in MOD_SUPPORTED_MODELS: | |
| raise ValueError("Current model is not supported by mixture-of-depth.") | |
| model = apply_mod_to_hf(model) | |
| model = model.to(model_args.compute_dtype) | |
| return model | |