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wehub-resource-sync a203934033
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chore: import upstream snapshot with attribution
2026-07-13 13:34:58 +08:00

113 lines
4.2 KiB
Python

# Copyright (c) ModelScope Contributors. All rights reserved.
from transformers import PreTrainedModel
from transformers.dynamic_module_utils import get_class_from_dynamic_module
from swift.template import TemplateType
from swift.utils import get_logger
from ..constant import LLMModelType, MLLMModelType
from ..model_arch import ModelArch
from ..model_meta import Model, ModelGroup, ModelMeta
from ..register import ModelLoader, register_model
logger = get_logger()
register_model(
ModelMeta(
LLMModelType.ernie4_5,
[
ModelGroup([
Model('PaddlePaddle/ERNIE-4.5-0.3B-Base-PT', 'baidu/ERNIE-4.5-0.3B-PT'),
Model('PaddlePaddle/ERNIE-4.5-0.3B-PT', 'baidu/ERNIE-4.5-0.3B-PT'),
], TemplateType.ernie),
],
architectures=['Ernie4_5_ForCausalLM'],
))
register_model(
ModelMeta(
LLMModelType.ernie4_5_moe,
[
ModelGroup([
Model('PaddlePaddle/ERNIE-4.5-21B-A3B-Base-PT', 'baidu/ERNIE-4.5-21B-A3B-Base-PT'),
Model('PaddlePaddle/ERNIE-4.5-21B-A3B-PT', 'baidu/ERNIE-4.5-21B-A3B-PT'),
Model('PaddlePaddle/ERNIE-4.5-300B-A47B-Base-PT', 'baidu/ERNIE-4.5-300B-A47B-Base-PT'),
Model('PaddlePaddle/ERNIE-4.5-300B-A47B-PT', 'baidu/ERNIE-4.5-300B-A47B-PT'),
], TemplateType.ernie),
ModelGroup([
Model('PaddlePaddle/ERNIE-4.5-21B-A3B-Thinking', 'baidu/ERNIE-4.5-21B-A3B-Thinking'),
], TemplateType.ernie_thinking),
],
architectures=['Ernie4_5_MoeForCausalLM'],
))
class ErnieVLLoader(ModelLoader):
def get_model(self, model_dir: str, config, processor, model_kwargs) -> PreTrainedModel:
MOEAllGatherLayerV2 = get_class_from_dynamic_module('modeling_ernie4_5_vl.MOEAllGatherLayerV2', model_dir)
self.leaf_modules = MOEAllGatherLayerV2
model = super().get_model(model_dir, config, processor, model_kwargs)
model.add_image_preprocess(processor)
return model
register_model(
ModelMeta(
MLLMModelType.ernie_vl,
[
ModelGroup([
Model('PaddlePaddle/ERNIE-4.5-VL-28B-A3B-PT', 'baidu/ERNIE-4.5-VL-28B-A3B-PT'),
Model('PaddlePaddle/ERNIE-4.5-VL-424B-A47B-PT', 'baidu/ERNIE-4.5-VL-424B-A47B-PT'),
Model('PaddlePaddle/ERNIE-4.5-VL-28B-A3B-Base-PT', 'baidu/ERNIE-4.5-VL-28B-A3B-Base-PT'),
Model('PaddlePaddle/ERNIE-4.5-VL-424B-A47B-Base-PT', 'baidu/ERNIE-4.5-VL-424B-A47B-Base-PT'),
], TemplateType.ernie_vl),
ModelGroup([
Model('PaddlePaddle/ERNIE-4.5-VL-28B-A3B-Thinking', 'baidu/ERNIE-4.5-VL-28B-A3B-Thinking'),
], TemplateType.ernie_vl_thinking),
],
ErnieVLLoader,
model_arch=ModelArch.ernie_vl,
architectures=['Ernie4_5_VLMoeForConditionalGeneration'],
requires=['transformers>=4.52', 'moviepy'],
))
register_model(
ModelMeta(
MLLMModelType.paddle_ocr,
[
ModelGroup([
Model('PaddlePaddle/PaddleOCR-VL', 'PaddlePaddle/PaddleOCR-VL'),
]),
],
template=TemplateType.paddle_ocr,
model_arch=ModelArch.keye_vl,
architectures=['PaddleOCRVLForConditionalGeneration'],
requires=['transformers<5.0'],
))
class PaddleOCR1_5Loader(ModelLoader):
default_trust_remote_code = False
def get_model(self, model_dir: str, *args, **kwargs) -> PreTrainedModel:
from transformers import AutoModelForImageTextToText
self.auto_model_cls = self.auto_model_cls or AutoModelForImageTextToText
return super().get_model(model_dir, *args, **kwargs)
register_model(
ModelMeta(
MLLMModelType.paddleocr_vl,
[
ModelGroup([
Model('PaddlePaddle/PaddleOCR-VL-1.5', 'PaddlePaddle/PaddleOCR-VL-1.5'),
Model('PaddlePaddle/PaddleOCR-VL-1.6', 'PaddlePaddle/PaddleOCR-VL-1.6'),
],
template=TemplateType.paddle_ocr_1_5),
],
PaddleOCR1_5Loader,
model_arch=ModelArch.paddleocr_vl,
requires=['transformers>=5.0'],
architectures=['PaddleOCRVLForConditionalGeneration'],
))