# Copyright (c) ModelScope Contributors. All rights reserved. from transformers import PretrainedConfig from typing import Any, Dict from swift.template import TemplateType from swift.utils import Processor from ..constant import LLMModelType, RMModelType from ..model_arch import ModelArch from ..model_meta import Model, ModelGroup, ModelMeta from ..register import ModelLoader, register_model class SkyworkLoader(ModelLoader): def get_processor(self, model_dir: str, config: PretrainedConfig) -> Processor: tokenizer = super().get_processor(model_dir, config) tokenizer.add_tokens('[USER]') tokenizer.add_tokens('[BOT]') tokenizer.add_tokens('[SEP]') return tokenizer register_model( ModelMeta( LLMModelType.skywork, [ ModelGroup([ Model('skywork/Skywork-13B-base', 'skywork/Skywork-13B-base'), Model('skywork/Skywork-13B-chat'), ]), ], template=TemplateType.skywork, architectures=['SkyworkForCausalLM'], model_arch=ModelArch.llama, )) register_model( ModelMeta( RMModelType.llama3_2_reward, [ ModelGroup([ Model('AI-ModelScope/Skywork-Reward-Llama-3.1-8B', 'Skywork/Skywork-Reward-Llama-3.1-8B'), Model('AI-ModelScope/Skywork-Reward-Llama-3.1-8B-v0.2', 'Skywork/Skywork-Reward-Llama-3.1-8B-v0.2'), ]), ModelGroup([ Model('AI-ModelScope/GRM_Llama3.1_8B_rewardmodel-ft', 'Ray2333/GRM_Llama3.1_8B_rewardmodel-ft'), Model('AI-ModelScope/GRM-llama3.2-3B-rewardmodel-ft', 'Ray2333/GRM-llama3.2-3B-rewardmodel-ft'), ]) ], template=TemplateType.llama3_2, requires=['transformers>=4.43'], architectures=['LlamaForSequenceClassification'], model_arch=ModelArch.llama, )) register_model( ModelMeta( RMModelType.gemma_reward, [ ModelGroup([ Model('AI-ModelScope/Skywork-Reward-Gemma-2-27B', 'Skywork/Skywork-Reward-Gemma-2-27B'), Model('AI-ModelScope/Skywork-Reward-Gemma-2-27B-v0.2', 'Skywork/Skywork-Reward-Gemma-2-27B-v0.2'), ]), ], template=TemplateType.gemma, requires=['transformers>=4.42'], architectures=['Gemma2ForSequenceClassification'], model_arch=ModelArch.llama, ))