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feat(transformers/models): add models of d_fine, granitemoehybrid and efficientloftr
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mindone/transformers/__init__.py

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)
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from .models.ctrl import CTRLForSequenceClassification, CTRLLMHeadModel, CTRLModel, CTRLPreTrainedModel
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from .models.cvt import CvtForImageClassification, CvtModel, CvtPreTrainedModel
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from .models.d_fine import DFineForObjectDetection, DFineModel, DFinePreTrainedModel
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from .models.dac import DacModel, DacPreTrainedModel
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from .models.data2vec import (
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Data2VecAudioForAudioFrameClassification,
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DPRReader,
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)
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from .models.dpt import DPTForDepthEstimation, DPTImageProcessor, DPTModel, DPTPreTrainedModel
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from .models.efficientloftr import EfficientLoFTRForKeypointMatching, EfficientLoFTRModel, EfficientLoFTRPreTrainedModel
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from .models.efficientnet import (
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EfficientNetForImageClassification,
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EfficientNetImageProcessor,
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)
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from .models.granite import GraniteForCausalLM, GraniteModel, GranitePreTrainedModel
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from .models.granitemoe import GraniteMoeForCausalLM, GraniteMoeModel, GraniteMoePreTrainedModel
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from .models.granitemoehybrid import GraniteMoeHybridForCausalLM, GraniteMoeHybridModel, GraniteMoeHybridPreTrainedModel
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from .models.granitemoeshared import GraniteMoeSharedForCausalLM, GraniteMoeSharedModel, GraniteMoeSharedPreTrainedModel
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from .models.grounding_dino import (
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GroundingDinoForObjectDetection,

mindone/transformers/models/__init__.py

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convnextv2,
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ctrl,
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cvt,
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d_fine,
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dac,
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data2vec,
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dbrx,
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distilbert,
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dpr,
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dpt,
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efficientloftr,
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efficientnet,
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electra,
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emu3,
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gptj,
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granite,
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granitemoe,
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granitemoehybrid,
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granitemoeshared,
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groupvit,
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hgnet_v2,

mindone/transformers/models/auto/image_processing_auto.py

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("owlv2", ("Owlv2ImageProcessor",)),
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("owlvit", ("OwlViTImageProcessor",)),
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("qwen2_5_vl", ("Qwen2VLImageProcessor",)),
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("rt_detr", ("RTDetrImageProcessor",)),
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("sam", ("SamImageProcessor",)),
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("segformer", ("SegformerImageProcessor",)),
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("siglip", ("SiglipImageProcessor", "SiglipImageProcessorFast")),
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# Copyright 2025 The HuggingFace Team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from .modeling_d_fine import *

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