# Copyright (c) ModelScope Contributors. All rights reserved. from transformers import PretrainedConfig, PreTrainedModel from types import MethodType from typing import Any, Dict from swift.template import TemplateType from swift.utils import Processor, get_device, get_env_args from ..constant import LLMModelType, MLLMModelType from ..model_arch import ModelArch from ..model_meta import Model, ModelGroup, ModelMeta from ..patcher import patch_ignore_check_imports, patch_output_clone from ..register import ModelLoader, register_model from ..utils import use_submodel_func class Phi3VisionLoader(ModelLoader): num_crops = 4 def get_processor(self, model_dir: str, config: PretrainedConfig) -> Processor: processor_kwargs = {'num_crops': get_env_args('num_crops', int, self.num_crops)} from transformers import AutoProcessor processor = AutoProcessor.from_pretrained(model_dir, trust_remote_code=True, **processor_kwargs) return processor def get_model(self, model_dir: str, *args, **kwargs) -> PreTrainedModel: model = super().get_model(model_dir, *args, **kwargs) patch_output_clone(model.model.vision_embed_tokens.wte) return model register_model( ModelMeta( MLLMModelType.phi3_vision, [ ModelGroup([ Model('LLM-Research/Phi-3-vision-128k-instruct', 'microsoft/Phi-3-vision-128k-instruct'), Model('LLM-Research/Phi-3.5-vision-instruct', 'microsoft/Phi-3.5-vision-instruct'), ]) ], Phi3VisionLoader, template=TemplateType.phi3_vision, architectures=['Phi3VForCausalLM'], model_arch=ModelArch.phi3_vision, requires=['transformers>=4.36'], tags=['vision'], )) class Phi4MultimodalLoader(ModelLoader): def get_processor(self, model_dir: str, config: PretrainedConfig) -> Processor: processor = super().get_processor(model_dir, config) processor.audio_processor.audio_compression_rate = processor.audio_processor.compression_rate processor.audio_processor.audio_downsample_rate = processor.audio_processor.qformer_compression_rate processor.audio_processor.audio_feat_stride = processor.audio_processor.feat_stride del processor.audio_processor.feature_size del processor.audio_processor.sampling_rate del processor.audio_processor.padding_value del processor.__class__.chat_template processor.chat_template = None return processor def get_model(self, model_dir: str, *args, **kwargs) -> PreTrainedModel: model = super().get_model(model_dir, *args, **kwargs) model.set_lora_adapter(['vision', 'speech']) return model register_model( ModelMeta( MLLMModelType.phi4_multimodal, [ModelGroup([ Model('LLM-Research/Phi-4-multimodal-instruct', 'microsoft/Phi-4-multimodal-instruct'), ])], Phi4MultimodalLoader, template=TemplateType.phi4_multimodal, architectures=['Phi4MMForCausalLM'], model_arch=ModelArch.phi4_multimodal, requires=['transformers>=4.36,<4.49', 'backoff', 'soundfile'], tags=['vision', 'audio'], )) class FlorenceLoader(ModelLoader): def get_model(self, model_dir: str, config, processor, model_kwargs) -> PreTrainedModel: config.vision_config.model_type = 'davit' # fix merge-lora if model_kwargs['device_map'] == 'auto': model_kwargs['device_map'] = get_device() with patch_ignore_check_imports(): model = super().get_model(model_dir, config, processor, model_kwargs) model.vision_tower.enable_checkpoint = True use_submodel_func(model, 'language_model', ['generate', 'forward']) return model register_model( ModelMeta( MLLMModelType.florence, [ # llama2 ModelGroup([ Model('AI-ModelScope/Florence-2-base-ft', 'microsoft/Florence-2-base-ft'), Model('AI-ModelScope/Florence-2-base', 'microsoft/Florence-2-base'), Model('AI-ModelScope/Florence-2-large', 'microsoft/Florence-2-large'), Model('AI-ModelScope/Florence-2-large-ft', 'microsoft/Florence-2-large-ft'), ]), ], FlorenceLoader, template=TemplateType.florence, architectures=['Florence2ForConditionalGeneration'], model_arch=ModelArch.florence, tags=['vision'], )) class Phi3SmallLoader(ModelLoader): def get_model(self, model_dir: str, *args, **kwargs) -> PreTrainedModel: model = super().get_model(model_dir, *args, **kwargs) def rotary_emb(self, query_states, key_states, **kwargs): q_type = query_states.dtype k_type = key_states.dtype query_states, key_states = self.rotory_emb_origin(query_states, key_states, **kwargs) query_states = query_states.to(q_type) key_states = key_states.to(k_type) return query_states, key_states for i in range(32): # TODO: 32 re = model.model.layers[i].self_attn.rotary_emb re.rotory_emb_origin = re.forward re.forward = MethodType(rotary_emb, re) return model register_model( ModelMeta( LLMModelType.phi3_small, [ ModelGroup([ Model('LLM-Research/Phi-3-small-8k-instruct', 'microsoft/Phi-3-small-8k-instruct'), Model('LLM-Research/Phi-3-small-128k-instruct', 'microsoft/Phi-3-small-128k-instruct'), ]), ], Phi3SmallLoader, template=TemplateType.phi3, architectures=['Phi3SmallForCausalLM'], model_arch=ModelArch.phi3_small, requires=['transformers>=4.36'], )) register_model( ModelMeta( LLMModelType.phi2, [ ModelGroup([ Model('AI-ModelScope/phi-2', 'microsoft/phi-2'), ]), ], template=TemplateType.default, architectures=['PhiForCausalLM'], model_arch=ModelArch.phi2, )) register_model( ModelMeta( LLMModelType.phi3, [ ModelGroup([ Model('LLM-Research/Phi-3-mini-4k-instruct', 'microsoft/Phi-3-mini-4k-instruct'), Model('LLM-Research/Phi-3-mini-128k-instruct', 'microsoft/Phi-3-mini-128k-instruct'), Model('LLM-Research/Phi-3-medium-4k-instruct', 'microsoft/Phi-3-medium-4k-instruct'), Model('LLM-Research/Phi-3-medium-128k-instruct', 'microsoft/Phi-3-medium-128k-instruct'), Model('LLM-Research/Phi-3.5-mini-instruct', 'microsoft/Phi-3.5-mini-instruct'), ]), ModelGroup([Model('LLM-Research/Phi-4-mini-instruct', 'microsoft/Phi-4-mini-instruct')]) ], template=TemplateType.phi3, architectures=['Phi3ForCausalLM'], requires=['transformers>=4.36'], model_arch=ModelArch.phi3, )) register_model( ModelMeta( LLMModelType.phi4, [ ModelGroup([ Model('LLM-Research/phi-4', 'microsoft/phi-4'), ]), ], template=TemplateType.phi4, architectures=['Phi3ForCausalLM'], requires=['transformers>=4.36'], model_arch=ModelArch.phi3, )) register_model( ModelMeta( LLMModelType.phi3_moe, [ ModelGroup([ Model('LLM-Research/Phi-3.5-MoE-instruct', 'microsoft/Phi-3.5-MoE-instruct'), ]), ], template=TemplateType.phi3, architectures=['PhiMoEForCausalLM'], requires=['transformers>=4.36'], ))