# coding=utf-8 # Copyright 2018 The HuggingFace Inc. 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. """Auto Model class.""" import warnings from collections import OrderedDict from ...utils import logging from .auto_factory import ( _BaseAutoBackboneClass, _BaseAutoModelClass, _LazyAutoMapping, auto_class_update, ) from .configuration_auto import CONFIG_MAPPING_NAMES logger = logging.get_logger(__name__) MODEL_MAPPING_NAMES = OrderedDict( [ # Base model mapping ("albert", "AlbertModel"), ("align", "AlignModel"), ("altclip", "AltCLIPModel"), ("aria", "AriaForConditionalGeneration"), ("aria_text", "AriaTextModel"), ("audio-spectrogram-transformer", "ASTModel"), ("autoformer", "AutoformerModel"), ("bamba", "BambaModel"), ("bark", "BarkModel"), ("bart", "BartModel"), ("beit", "BeitModel"), ("bert", "BertModel"), ("bert-generation", "BertGenerationEncoder"), ("big_bird", "BigBirdModel"), ("bigbird_pegasus", "BigBirdPegasusModel"), ("biogpt", "BioGptModel"), ("bit", "BitModel"), ("blenderbot", "BlenderbotModel"), ("blenderbot-small", "BlenderbotSmallModel"), ("blip", "BlipModel"), ("blip-2", "Blip2Model"), ("bloom", "BloomModel"), ("bridgetower", "BridgeTowerModel"), ("bros", "BrosModel"), ("camembert", "CamembertModel"), ("canine", "CanineModel"), ("chameleon", "ChameleonModel"), ("chinese_clip", "ChineseCLIPModel"), ("chinese_clip_vision_model", "ChineseCLIPVisionModel"), ("clap", "ClapModel"), ("clip", "CLIPModel"), ("clip_text_model", "CLIPTextModel"), ("clip_vision_model", "CLIPVisionModel"), ("clipseg", "CLIPSegModel"), ("clvp", "ClvpModelForConditionalGeneration"), ("code_llama", "LlamaModel"), ("codegen", "CodeGenModel"), ("cohere", "CohereModel"), ("cohere2", "Cohere2Model"), ("conditional_detr", "ConditionalDetrModel"), ("convbert", "ConvBertModel"), ("convnext", "ConvNextModel"), ("convnextv2", "ConvNextV2Model"), ("cpmant", "CpmAntModel"), ("ctrl", "CTRLModel"), ("cvt", "CvtModel"), ("dab-detr", "DabDetrModel"), ("dac", "DacModel"), ("data2vec-audio", "Data2VecAudioModel"), ("data2vec-text", "Data2VecTextModel"), ("data2vec-vision", "Data2VecVisionModel"), ("dbrx", "DbrxModel"), ("deberta", "DebertaModel"), ("deberta-v2", "DebertaV2Model"), ("decision_transformer", "DecisionTransformerModel"), ("deepseek_v3", "DeepseekV3Model"), ("deformable_detr", "DeformableDetrModel"), ("deit", "DeiTModel"), ("depth_pro", "DepthProModel"), ("deta", "DetaModel"), ("detr", "DetrModel"), ("diffllama", "DiffLlamaModel"), ("dinat", "DinatModel"), ("dinov2", "Dinov2Model"), ("dinov2_with_registers", "Dinov2WithRegistersModel"), ("distilbert", "DistilBertModel"), ("donut-swin", "DonutSwinModel"), ("dpr", "DPRQuestionEncoder"), ("dpt", "DPTModel"), ("efficientformer", "EfficientFormerModel"), ("efficientnet", "EfficientNetModel"), ("electra", "ElectraModel"), ("encodec", "EncodecModel"), ("ernie", "ErnieModel"), ("ernie_m", "ErnieMModel"), ("esm", "EsmModel"), ("falcon", "FalconModel"), ("falcon_mamba", "FalconMambaModel"), ("fastspeech2_conformer", "FastSpeech2ConformerModel"), ("flaubert", "FlaubertModel"), ("flava", "FlavaModel"), ("fnet", "FNetModel"), ("focalnet", "FocalNetModel"), ("fsmt", "FSMTModel"), ("funnel", ("FunnelModel", "FunnelBaseModel")), ("gemma", "GemmaModel"), ("gemma2", "Gemma2Model"), ("gemma3_text", "Gemma3TextModel"), ("git", "GitModel"), ("glm", "GlmModel"), ("glm4", "Glm4Model"), ("glpn", "GLPNModel"), ("got_ocr2", "GotOcr2ForConditionalGeneration"), ("gpt-sw3", "GPT2Model"), ("gpt2", "GPT2Model"), ("gpt_bigcode", "GPTBigCodeModel"), ("gpt_neo", "GPTNeoModel"), ("gpt_neox", "GPTNeoXModel"), ("gpt_neox_japanese", "GPTNeoXJapaneseModel"), ("gptj", "GPTJModel"), ("gptsan-japanese", "GPTSanJapaneseForConditionalGeneration"), ("granite", "GraniteModel"), ("granitemoe", "GraniteMoeModel"), ("granitemoeshared", "GraniteMoeSharedModel"), ("graphormer", "GraphormerModel"), ("grounding-dino", "GroundingDinoModel"), ("groupvit", "GroupViTModel"), ("helium", "HeliumModel"), ("hiera", "HieraModel"), ("hubert", "HubertModel"), ("ibert", "IBertModel"), ("idefics", "IdeficsModel"), ("idefics2", "Idefics2Model"), ("idefics3", "Idefics3Model"), ("idefics3_vision", "Idefics3VisionTransformer"), ("ijepa", "IJepaModel"), ("imagegpt", "ImageGPTModel"), ("informer", "InformerModel"), ("jamba", "JambaModel"), ("jetmoe", "JetMoeModel"), ("jukebox", "JukeboxModel"), ("kosmos-2", "Kosmos2Model"), ("layoutlm", "LayoutLMModel"), ("layoutlmv2", "LayoutLMv2Model"), ("layoutlmv3", "LayoutLMv3Model"), ("led", "LEDModel"), ("levit", "LevitModel"), ("lilt", "LiltModel"), ("llama", "LlamaModel"), ("llama4", "Llama4ForConditionalGeneration"), ("longformer", "LongformerModel"), ("longt5", "LongT5Model"), ("luke", "LukeModel"), ("lxmert", "LxmertModel"), ("m2m_100", "M2M100Model"), ("mamba", "MambaModel"), ("mamba2", "Mamba2Model"), ("marian", "MarianModel"), ("markuplm", "MarkupLMModel"), ("mask2former", "Mask2FormerModel"), ("maskformer", "MaskFormerModel"), ("maskformer-swin", "MaskFormerSwinModel"), ("mbart", "MBartModel"), ("mctct", "MCTCTModel"), ("mega", "MegaModel"), ("megatron-bert", "MegatronBertModel"), ("mgp-str", "MgpstrForSceneTextRecognition"), ("mimi", "MimiModel"), ("mistral", "MistralModel"), ("mixtral", "MixtralModel"), ("mobilebert", "MobileBertModel"), ("mobilenet_v1", "MobileNetV1Model"), ("mobilenet_v2", "MobileNetV2Model"), ("mobilevit", "MobileViTModel"), ("mobilevitv2", "MobileViTV2Model"), ("modernbert", "ModernBertModel"), ("moonshine", "MoonshineModel"), ("moshi", "MoshiModel"), ("mpnet", "MPNetModel"), ("mpt", "MptModel"), ("mra", "MraModel"), ("mt5", "MT5Model"), ("musicgen", "MusicgenModel"), ("musicgen_melody", "MusicgenMelodyModel"), ("mvp", "MvpModel"), ("nat", "NatModel"), ("nemotron", "NemotronModel"), ("nezha", "NezhaModel"), ("nllb-moe", "NllbMoeModel"), ("nystromformer", "NystromformerModel"), ("olmo", "OlmoModel"), ("olmo2", "Olmo2Model"), ("olmoe", "OlmoeModel"), ("omdet-turbo", "OmDetTurboForObjectDetection"), ("oneformer", "OneFormerModel"), ("open-llama", "OpenLlamaModel"), ("openai-gpt", "OpenAIGPTModel"), ("opt", "OPTModel"), ("owlv2", "Owlv2Model"), ("owlvit", "OwlViTModel"), ("patchtsmixer", "PatchTSMixerModel"), ("patchtst", "PatchTSTModel"), ("pegasus", "PegasusModel"), ("pegasus_x", "PegasusXModel"), ("perceiver", "PerceiverModel"), ("persimmon", "PersimmonModel"), ("phi", "PhiModel"), ("phi3", "Phi3Model"), ("phi4_multimodal", "Phi4MultimodalModel"), ("phimoe", "PhimoeModel"), ("pixtral", "PixtralVisionModel"), ("plbart", "PLBartModel"), ("poolformer", "PoolFormerModel"), ("prophetnet", "ProphetNetModel"), ("pvt", "PvtModel"), ("pvt_v2", "PvtV2Model"), ("qdqbert", "QDQBertModel"), ("qwen2", "Qwen2Model"), ("qwen2_5_vl", "Qwen2_5_VLModel"), ("qwen2_audio_encoder", "Qwen2AudioEncoder"), ("qwen2_moe", "Qwen2MoeModel"), ("qwen2_vl", "Qwen2VLModel"), ("qwen3", "Qwen3Model"), ("qwen3_moe", "Qwen3MoeModel"), ("recurrent_gemma", "RecurrentGemmaModel"), ("reformer", "ReformerModel"), ("regnet", "RegNetModel"), ("rembert", "RemBertModel"), ("resnet", "ResNetModel"), ("retribert", "RetriBertModel"), ("roberta", "RobertaModel"), ("roberta-prelayernorm", "RobertaPreLayerNormModel"), ("roc_bert", "RoCBertModel"), ("roformer", "RoFormerModel"), ("rt_detr", "RTDetrModel"), ("rt_detr_v2", "RTDetrV2Model"), ("rwkv", "RwkvModel"), ("sam", "SamModel"), ("sam_vision_model", "SamVisionModel"), ("seamless_m4t", "SeamlessM4TModel"), ("seamless_m4t_v2", "SeamlessM4Tv2Model"), ("segformer", "SegformerModel"), ("seggpt", "SegGptModel"), ("sew", "SEWModel"), ("sew-d", "SEWDModel"), ("siglip", "SiglipModel"), ("siglip2", "Siglip2Model"), ("siglip_vision_model", "SiglipVisionModel"), ("smolvlm", "SmolVLMModel"), ("smolvlm_vision", "SmolVLMVisionTransformer"), ("speech_to_text", "Speech2TextModel"), ("speecht5", "SpeechT5Model"), ("splinter", "SplinterModel"), ("squeezebert", "SqueezeBertModel"), ("stablelm", "StableLmModel"), ("starcoder2", "Starcoder2Model"), ("superglue", "SuperGlueForKeypointMatching"), ("swiftformer", "SwiftFormerModel"), ("swin", "SwinModel"), ("swin2sr", "Swin2SRModel"), ("swinv2", "Swinv2Model"), ("switch_transformers", "SwitchTransformersModel"), ("t5", "T5Model"), ("table-transformer", "TableTransformerModel"), ("tapas", "TapasModel"), ("textnet", "TextNetModel"), ("time_series_transformer", "TimeSeriesTransformerModel"), ("timesformer", "TimesformerModel"), ("timm_backbone", "TimmBackbone"), ("timm_wrapper", "TimmWrapperModel"), ("trajectory_transformer", "TrajectoryTransformerModel"), ("transfo-xl", "TransfoXLModel"), ("tvlt", "TvltModel"), ("tvp", "TvpModel"), ("udop", "UdopModel"), ("umt5", "UMT5Model"), ("unispeech", "UniSpeechModel"), ("unispeech-sat", "UniSpeechSatModel"), ("univnet", "UnivNetModel"), ("van", "VanModel"), ("videomae", "VideoMAEModel"), ("vilt", "ViltModel"), ("vision-text-dual-encoder", "VisionTextDualEncoderModel"), ("visual_bert", "VisualBertModel"), ("vit", "ViTModel"), ("vit_hybrid", "ViTHybridModel"), ("vit_mae", "ViTMAEModel"), ("vit_msn", "ViTMSNModel"), ("vitdet", "VitDetModel"), ("vits", "VitsModel"), ("vivit", "VivitModel"), ("wav2vec2", "Wav2Vec2Model"), ("wav2vec2-bert", "Wav2Vec2BertModel"), ("wav2vec2-conformer", "Wav2Vec2ConformerModel"), ("wavlm", "WavLMModel"), ("whisper", "WhisperModel"), ("xclip", "XCLIPModel"), ("xglm", "XGLMModel"), ("xlm", "XLMModel"), ("xlm-prophetnet", "XLMProphetNetModel"), ("xlm-roberta", "XLMRobertaModel"), ("xlm-roberta-xl", "XLMRobertaXLModel"), ("xlnet", "XLNetModel"), ("xmod", "XmodModel"), ("yolos", "YolosModel"), ("yoso", "YosoModel"), ("zamba", "ZambaModel"), ("zamba2", "Zamba2Model"), ] ) MODEL_FOR_PRETRAINING_MAPPING_NAMES = OrderedDict( [ # Model for pre-training mapping ("albert", "AlbertForPreTraining"), ("bart", "BartForConditionalGeneration"), ("bert", "BertForPreTraining"), ("big_bird", "BigBirdForPreTraining"), ("bloom", "BloomForCausalLM"), ("camembert", "CamembertForMaskedLM"), ("colpali", "ColPaliForRetrieval"), ("ctrl", "CTRLLMHeadModel"), ("data2vec-text", "Data2VecTextForMaskedLM"), ("deberta", "DebertaForMaskedLM"), ("deberta-v2", "DebertaV2ForMaskedLM"), ("distilbert", "DistilBertForMaskedLM"), ("electra", "ElectraForPreTraining"), ("ernie", "ErnieForPreTraining"), ("falcon_mamba", "FalconMambaForCausalLM"), ("flaubert", "FlaubertWithLMHeadModel"), ("flava", "FlavaForPreTraining"), ("fnet", "FNetForPreTraining"), ("fsmt", "FSMTForConditionalGeneration"), ("funnel", "FunnelForPreTraining"), ("gemma3", "Gemma3ForConditionalGeneration"), ("gpt-sw3", "GPT2LMHeadModel"), ("gpt2", "GPT2LMHeadModel"), ("gpt_bigcode", "GPTBigCodeForCausalLM"), ("gptsan-japanese", "GPTSanJapaneseForConditionalGeneration"), ("hiera", "HieraForPreTraining"), ("ibert", "IBertForMaskedLM"), ("idefics", "IdeficsForVisionText2Text"), ("idefics2", "Idefics2ForConditionalGeneration"), ("idefics3", "Idefics3ForConditionalGeneration"), ("layoutlm", "LayoutLMForMaskedLM"), ("llava", "LlavaForConditionalGeneration"), ("llava_next", "LlavaNextForConditionalGeneration"), ("llava_next_video", "LlavaNextVideoForConditionalGeneration"), ("llava_onevision", "LlavaOnevisionForConditionalGeneration"), ("longformer", "LongformerForMaskedLM"), ("luke", "LukeForMaskedLM"), ("lxmert", "LxmertForPreTraining"), ("mamba", "MambaForCausalLM"), ("mamba2", "Mamba2ForCausalLM"), ("mega", "MegaForMaskedLM"), ("megatron-bert", "MegatronBertForPreTraining"), ("mistral3", "Mistral3ForConditionalGeneration"), ("mllama", "MllamaForConditionalGeneration"), ("mobilebert", "MobileBertForPreTraining"), ("mpnet", "MPNetForMaskedLM"), ("mpt", "MptForCausalLM"), ("mra", "MraForMaskedLM"), ("mvp", "MvpForConditionalGeneration"), ("nezha", "NezhaForPreTraining"), ("nllb-moe", "NllbMoeForConditionalGeneration"), ("openai-gpt", "OpenAIGPTLMHeadModel"), ("paligemma", "PaliGemmaForConditionalGeneration"), ("qwen2_audio", "Qwen2AudioForConditionalGeneration"), ("retribert", "RetriBertModel"), ("roberta", "RobertaForMaskedLM"), ("roberta-prelayernorm", "RobertaPreLayerNormForMaskedLM"), ("roc_bert", "RoCBertForPreTraining"), ("rwkv", "RwkvForCausalLM"), ("splinter", "SplinterForPreTraining"), ("squeezebert", "SqueezeBertForMaskedLM"), ("switch_transformers", "SwitchTransformersForConditionalGeneration"), ("t5", "T5ForConditionalGeneration"), ("tapas", "TapasForMaskedLM"), ("transfo-xl", "TransfoXLLMHeadModel"), ("tvlt", "TvltForPreTraining"), ("unispeech", "UniSpeechForPreTraining"), ("unispeech-sat", "UniSpeechSatForPreTraining"), ("video_llava", "VideoLlavaForConditionalGeneration"), ("videomae", "VideoMAEForPreTraining"), ("vipllava", "VipLlavaForConditionalGeneration"), ("visual_bert", "VisualBertForPreTraining"), ("vit_mae", "ViTMAEForPreTraining"), ("wav2vec2", "Wav2Vec2ForPreTraining"), ("wav2vec2-conformer", "Wav2Vec2ConformerForPreTraining"), ("xlm", "XLMWithLMHeadModel"), ("xlm-roberta", "XLMRobertaForMaskedLM"), ("xlm-roberta-xl", "XLMRobertaXLForMaskedLM"), ("xlnet", "XLNetLMHeadModel"), ("xmod", "XmodForMaskedLM"), ] ) MODEL_WITH_LM_HEAD_MAPPING_NAMES = OrderedDict( [ # Model with LM heads mapping ("albert", "AlbertForMaskedLM"), ("bart", "BartForConditionalGeneration"), ("bert", "BertForMaskedLM"), ("big_bird", "BigBirdForMaskedLM"), ("bigbird_pegasus", "BigBirdPegasusForConditionalGeneration"), ("blenderbot-small", "BlenderbotSmallForConditionalGeneration"), ("bloom", "BloomForCausalLM"), ("camembert", "CamembertForMaskedLM"), ("codegen", "CodeGenForCausalLM"), ("convbert", "ConvBertForMaskedLM"), ("cpmant", "CpmAntForCausalLM"), ("ctrl", "CTRLLMHeadModel"), ("data2vec-text", "Data2VecTextForMaskedLM"), ("deberta", "DebertaForMaskedLM"), ("deberta-v2", "DebertaV2ForMaskedLM"), ("distilbert", "DistilBertForMaskedLM"), ("electra", "ElectraForMaskedLM"), ("encoder-decoder", "EncoderDecoderModel"), ("ernie", "ErnieForMaskedLM"), ("esm", "EsmForMaskedLM"), ("falcon_mamba", "FalconMambaForCausalLM"), ("flaubert", "FlaubertWithLMHeadModel"), ("fnet", "FNetForMaskedLM"), ("fsmt", "FSMTForConditionalGeneration"), ("funnel", "FunnelForMaskedLM"), ("git", "GitForCausalLM"), ("gpt-sw3", "GPT2LMHeadModel"), ("gpt2", "GPT2LMHeadModel"), ("gpt_bigcode", "GPTBigCodeForCausalLM"), ("gpt_neo", "GPTNeoForCausalLM"), ("gpt_neox", "GPTNeoXForCausalLM"), ("gpt_neox_japanese", "GPTNeoXJapaneseForCausalLM"), ("gptj", "GPTJForCausalLM"), ("gptsan-japanese", "GPTSanJapaneseForConditionalGeneration"), ("ibert", "IBertForMaskedLM"), ("layoutlm", "LayoutLMForMaskedLM"), ("led", "LEDForConditionalGeneration"), ("longformer", "LongformerForMaskedLM"), ("longt5", "LongT5ForConditionalGeneration"), ("luke", "LukeForMaskedLM"), ("m2m_100", "M2M100ForConditionalGeneration"), ("mamba", "MambaForCausalLM"), ("mamba2", "Mamba2ForCausalLM"), ("marian", "MarianMTModel"), ("mega", "MegaForMaskedLM"), ("megatron-bert", "MegatronBertForCausalLM"), ("mobilebert", "MobileBertForMaskedLM"), ("moonshine", "MoonshineForConditionalGeneration"), ("mpnet", "MPNetForMaskedLM"), ("mpt", "MptForCausalLM"), ("mra", "MraForMaskedLM"), ("mvp", "MvpForConditionalGeneration"), ("nezha", "NezhaForMaskedLM"), ("nllb-moe", "NllbMoeForConditionalGeneration"), ("nystromformer", "NystromformerForMaskedLM"), ("openai-gpt", "OpenAIGPTLMHeadModel"), ("pegasus_x", "PegasusXForConditionalGeneration"), ("plbart", "PLBartForConditionalGeneration"), ("pop2piano", "Pop2PianoForConditionalGeneration"), ("qdqbert", "QDQBertForMaskedLM"), ("reformer", "ReformerModelWithLMHead"), ("rembert", "RemBertForMaskedLM"), ("roberta", "RobertaForMaskedLM"), ("roberta-prelayernorm", "RobertaPreLayerNormForMaskedLM"), ("roc_bert", "RoCBertForMaskedLM"), ("roformer", "RoFormerForMaskedLM"), ("rwkv", "RwkvForCausalLM"), ("speech_to_text", "Speech2TextForConditionalGeneration"), ("squeezebert", "SqueezeBertForMaskedLM"), ("switch_transformers", "SwitchTransformersForConditionalGeneration"), ("t5", "T5ForConditionalGeneration"), ("tapas", "TapasForMaskedLM"), ("transfo-xl", "TransfoXLLMHeadModel"), ("wav2vec2", "Wav2Vec2ForMaskedLM"), ("whisper", "WhisperForConditionalGeneration"), ("xlm", "XLMWithLMHeadModel"), ("xlm-roberta", "XLMRobertaForMaskedLM"), ("xlm-roberta-xl", "XLMRobertaXLForMaskedLM"), ("xlnet", "XLNetLMHeadModel"), ("xmod", "XmodForMaskedLM"), ("yoso", "YosoForMaskedLM"), ] ) MODEL_FOR_CAUSAL_LM_MAPPING_NAMES = OrderedDict( [ # Model for Causal LM mapping ("aria_text", "AriaTextForCausalLM"), ("bamba", "BambaForCausalLM"), ("bart", "BartForCausalLM"), ("bert", "BertLMHeadModel"), ("bert-generation", "BertGenerationDecoder"), ("big_bird", "BigBirdForCausalLM"), ("bigbird_pegasus", "BigBirdPegasusForCausalLM"), ("biogpt", "BioGptForCausalLM"), ("blenderbot", "BlenderbotForCausalLM"), ("blenderbot-small", "BlenderbotSmallForCausalLM"), ("bloom", "BloomForCausalLM"), ("camembert", "CamembertForCausalLM"), ("code_llama", "LlamaForCausalLM"), ("codegen", "CodeGenForCausalLM"), ("cohere", "CohereForCausalLM"), ("cohere2", "Cohere2ForCausalLM"), ("cpmant", "CpmAntForCausalLM"), ("ctrl", "CTRLLMHeadModel"), ("data2vec-text", "Data2VecTextForCausalLM"), ("dbrx", "DbrxForCausalLM"), ("deepseek_v3", "DeepseekV3ForCausalLM"), ("diffllama", "DiffLlamaForCausalLM"), ("electra", "ElectraForCausalLM"), ("emu3", "Emu3ForCausalLM"), ("ernie", "ErnieForCausalLM"), ("falcon", "FalconForCausalLM"), ("falcon_mamba", "FalconMambaForCausalLM"), ("fuyu", "FuyuForCausalLM"), ("gemma", "GemmaForCausalLM"), ("gemma2", "Gemma2ForCausalLM"), ("gemma3", "Gemma3ForConditionalGeneration"), ("gemma3_text", "Gemma3ForCausalLM"), ("git", "GitForCausalLM"), ("glm", "GlmForCausalLM"), ("glm4", "Glm4ForCausalLM"), ("got_ocr2", "GotOcr2ForConditionalGeneration"), ("gpt-sw3", "GPT2LMHeadModel"), ("gpt2", "GPT2LMHeadModel"), ("gpt_bigcode", "GPTBigCodeForCausalLM"), ("gpt_neo", "GPTNeoForCausalLM"), ("gpt_neox", "GPTNeoXForCausalLM"), ("gpt_neox_japanese", "GPTNeoXJapaneseForCausalLM"), ("gptj", "GPTJForCausalLM"), ("granite", "GraniteForCausalLM"), ("granitemoe", "GraniteMoeForCausalLM"), ("granitemoeshared", "GraniteMoeSharedForCausalLM"), ("helium", "HeliumForCausalLM"), ("jamba", "JambaForCausalLM"), ("jetmoe", "JetMoeForCausalLM"), ("llama", "LlamaForCausalLM"), ("llama4", "Llama4ForCausalLM"), ("llama4_text", "Llama4ForCausalLM"), ("mamba", "MambaForCausalLM"), ("mamba2", "Mamba2ForCausalLM"), ("marian", "MarianForCausalLM"), ("mbart", "MBartForCausalLM"), ("mega", "MegaForCausalLM"), ("megatron-bert", "MegatronBertForCausalLM"), ("mistral", "MistralForCausalLM"), ("mixtral", "MixtralForCausalLM"), ("mllama", "MllamaForCausalLM"), ("moshi", "MoshiForCausalLM"), ("mpt", "MptForCausalLM"), ("musicgen", "MusicgenForCausalLM"), ("musicgen_melody", "MusicgenMelodyForCausalLM"), ("mvp", "MvpForCausalLM"), ("nemotron", "NemotronForCausalLM"), ("olmo", "OlmoForCausalLM"), ("olmo2", "Olmo2ForCausalLM"), ("olmoe", "OlmoeForCausalLM"), ("open-llama", "OpenLlamaForCausalLM"), ("openai-gpt", "OpenAIGPTLMHeadModel"), ("opt", "OPTForCausalLM"), ("pegasus", "PegasusForCausalLM"), ("persimmon", "PersimmonForCausalLM"), ("phi", "PhiForCausalLM"), ("phi3", "Phi3ForCausalLM"), ("phi4_multimodal", "Phi4MultimodalForCausalLM"), ("phimoe", "PhimoeForCausalLM"), ("plbart", "PLBartForCausalLM"), ("prophetnet", "ProphetNetForCausalLM"), ("qdqbert", "QDQBertLMHeadModel"), ("qwen2", "Qwen2ForCausalLM"), ("qwen2_moe", "Qwen2MoeForCausalLM"), ("qwen3", "Qwen3ForCausalLM"), ("qwen3_moe", "Qwen3MoeForCausalLM"), ("recurrent_gemma", "RecurrentGemmaForCausalLM"), ("reformer", "ReformerModelWithLMHead"), ("rembert", "RemBertForCausalLM"), ("roberta", "RobertaForCausalLM"), ("roberta-prelayernorm", "RobertaPreLayerNormForCausalLM"), ("roc_bert", "RoCBertForCausalLM"), ("roformer", "RoFormerForCausalLM"), ("rwkv", "RwkvForCausalLM"), ("speech_to_text_2", "Speech2Text2ForCausalLM"), ("stablelm", "StableLmForCausalLM"), ("starcoder2", "Starcoder2ForCausalLM"), ("transfo-xl", "TransfoXLLMHeadModel"), ("trocr", "TrOCRForCausalLM"), ("whisper", "WhisperForCausalLM"), ("xglm", "XGLMForCausalLM"), ("xlm", "XLMWithLMHeadModel"), ("xlm-prophetnet", "XLMProphetNetForCausalLM"), ("xlm-roberta", "XLMRobertaForCausalLM"), ("xlm-roberta-xl", "XLMRobertaXLForCausalLM"), ("xlnet", "XLNetLMHeadModel"), ("xmod", "XmodForCausalLM"), ("zamba", "ZambaForCausalLM"), ("zamba2", "Zamba2ForCausalLM"), ] ) MODEL_FOR_IMAGE_MAPPING_NAMES = OrderedDict( [ # Model for Image mapping ("beit", "BeitModel"), ("bit", "BitModel"), ("conditional_detr", "ConditionalDetrModel"), ("convnext", "ConvNextModel"), ("convnextv2", "ConvNextV2Model"), ("dab-detr", "DabDetrModel"), ("data2vec-vision", "Data2VecVisionModel"), ("deformable_detr", "DeformableDetrModel"), ("deit", "DeiTModel"), ("depth_pro", "DepthProModel"), ("deta", "DetaModel"), ("detr", "DetrModel"), ("dinat", "DinatModel"), ("dinov2", "Dinov2Model"), ("dinov2_with_registers", "Dinov2WithRegistersModel"), ("dpt", "DPTModel"), ("efficientformer", "EfficientFormerModel"), ("efficientnet", "EfficientNetModel"), ("focalnet", "FocalNetModel"), ("glpn", "GLPNModel"), ("hiera", "HieraModel"), ("ijepa", "IJepaModel"), ("imagegpt", "ImageGPTModel"), ("levit", "LevitModel"), ("llama4", "Llama4VisionModel"), ("mllama", "MllamaVisionModel"), ("mobilenet_v1", "MobileNetV1Model"), ("mobilenet_v2", "MobileNetV2Model"), ("mobilevit", "MobileViTModel"), ("mobilevitv2", "MobileViTV2Model"), ("nat", "NatModel"), ("poolformer", "PoolFormerModel"), ("pvt", "PvtModel"), ("regnet", "RegNetModel"), ("resnet", "ResNetModel"), ("segformer", "SegformerModel"), ("siglip_vision_model", "SiglipVisionModel"), ("swiftformer", "SwiftFormerModel"), ("swin", "SwinModel"), ("swin2sr", "Swin2SRModel"), ("swinv2", "Swinv2Model"), ("table-transformer", "TableTransformerModel"), ("timesformer", "TimesformerModel"), ("timm_backbone", "TimmBackbone"), ("timm_wrapper", "TimmWrapperModel"), ("van", "VanModel"), ("videomae", "VideoMAEModel"), ("vit", "ViTModel"), ("vit_hybrid", "ViTHybridModel"), ("vit_mae", "ViTMAEModel"), ("vit_msn", "ViTMSNModel"), ("vitdet", "VitDetModel"), ("vivit", "VivitModel"), ("yolos", "YolosModel"), ] ) MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING_NAMES = OrderedDict( [ ("deit", "DeiTForMaskedImageModeling"), ("focalnet", "FocalNetForMaskedImageModeling"), ("swin", "SwinForMaskedImageModeling"), ("swinv2", "Swinv2ForMaskedImageModeling"), ("vit", "ViTForMaskedImageModeling"), ] ) MODEL_FOR_CAUSAL_IMAGE_MODELING_MAPPING_NAMES = OrderedDict( # Model for Causal Image Modeling mapping [ ("imagegpt", "ImageGPTForCausalImageModeling"), ] ) MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES = OrderedDict( [ # Model for Image Classification mapping ("beit", "BeitForImageClassification"), ("bit", "BitForImageClassification"), ("clip", "CLIPForImageClassification"), ("convnext", "ConvNextForImageClassification"), ("convnextv2", "ConvNextV2ForImageClassification"), ("cvt", "CvtForImageClassification"), ("data2vec-vision", "Data2VecVisionForImageClassification"), ( "deit", ("DeiTForImageClassification", "DeiTForImageClassificationWithTeacher"), ), ("dinat", "DinatForImageClassification"), ("dinov2", "Dinov2ForImageClassification"), ("dinov2_with_registers", "Dinov2WithRegistersForImageClassification"), ( "efficientformer", ( "EfficientFormerForImageClassification", "EfficientFormerForImageClassificationWithTeacher", ), ), ("efficientnet", "EfficientNetForImageClassification"), ("focalnet", "FocalNetForImageClassification"), ("hiera", "HieraForImageClassification"), ("ijepa", "IJepaForImageClassification"), ("imagegpt", "ImageGPTForImageClassification"), ( "levit", ("LevitForImageClassification", "LevitForImageClassificationWithTeacher"), ), ("mobilenet_v1", "MobileNetV1ForImageClassification"), ("mobilenet_v2", "MobileNetV2ForImageClassification"), ("mobilevit", "MobileViTForImageClassification"), ("mobilevitv2", "MobileViTV2ForImageClassification"), ("nat", "NatForImageClassification"), ( "perceiver", ( "PerceiverForImageClassificationLearned", "PerceiverForImageClassificationFourier", "PerceiverForImageClassificationConvProcessing", ), ), ("poolformer", "PoolFormerForImageClassification"), ("pvt", "PvtForImageClassification"), ("pvt_v2", "PvtV2ForImageClassification"), ("regnet", "RegNetForImageClassification"), ("resnet", "ResNetForImageClassification"), ("segformer", "SegformerForImageClassification"), ("shieldgemma2", "ShieldGemma2ForImageClassification"), ("siglip", "SiglipForImageClassification"), ("siglip2", "Siglip2ForImageClassification"), ("swiftformer", "SwiftFormerForImageClassification"), ("swin", "SwinForImageClassification"), ("swinv2", "Swinv2ForImageClassification"), ("textnet", "TextNetForImageClassification"), ("timm_wrapper", "TimmWrapperForImageClassification"), ("van", "VanForImageClassification"), ("vit", "ViTForImageClassification"), ("vit_hybrid", "ViTHybridForImageClassification"), ("vit_msn", "ViTMSNForImageClassification"), ] ) MODEL_FOR_IMAGE_SEGMENTATION_MAPPING_NAMES = OrderedDict( [ # Do not add new models here, this class will be deprecated in the future. # Model for Image Segmentation mapping ("detr", "DetrForSegmentation"), ] ) MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING_NAMES = OrderedDict( [ # Model for Semantic Segmentation mapping ("beit", "BeitForSemanticSegmentation"), ("data2vec-vision", "Data2VecVisionForSemanticSegmentation"), ("dpt", "DPTForSemanticSegmentation"), ("mobilenet_v2", "MobileNetV2ForSemanticSegmentation"), ("mobilevit", "MobileViTForSemanticSegmentation"), ("mobilevitv2", "MobileViTV2ForSemanticSegmentation"), ("segformer", "SegformerForSemanticSegmentation"), ("upernet", "UperNetForSemanticSegmentation"), ] ) MODEL_FOR_INSTANCE_SEGMENTATION_MAPPING_NAMES = OrderedDict( [ # Model for Instance Segmentation mapping # MaskFormerForInstanceSegmentation can be removed from this mapping in v5 ("maskformer", "MaskFormerForInstanceSegmentation"), ] ) MODEL_FOR_UNIVERSAL_SEGMENTATION_MAPPING_NAMES = OrderedDict( [ # Model for Universal Segmentation mapping ("detr", "DetrForSegmentation"), ("mask2former", "Mask2FormerForUniversalSegmentation"), ("maskformer", "MaskFormerForInstanceSegmentation"), ("oneformer", "OneFormerForUniversalSegmentation"), ] ) MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING_NAMES = OrderedDict( [ ("timesformer", "TimesformerForVideoClassification"), ("videomae", "VideoMAEForVideoClassification"), ("vivit", "VivitForVideoClassification"), ] ) MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES = OrderedDict( [ ("blip", "BlipForConditionalGeneration"), ("blip-2", "Blip2ForConditionalGeneration"), ("chameleon", "ChameleonForConditionalGeneration"), ("git", "GitForCausalLM"), ("idefics2", "Idefics2ForConditionalGeneration"), ("idefics3", "Idefics3ForConditionalGeneration"), ("instructblip", "InstructBlipForConditionalGeneration"), ("instructblipvideo", "InstructBlipVideoForConditionalGeneration"), ("kosmos-2", "Kosmos2ForConditionalGeneration"), ("llava", "LlavaForConditionalGeneration"), ("llava_next", "LlavaNextForConditionalGeneration"), ("llava_next_video", "LlavaNextVideoForConditionalGeneration"), ("llava_onevision", "LlavaOnevisionForConditionalGeneration"), ("mistral3", "Mistral3ForConditionalGeneration"), ("mllama", "MllamaForConditionalGeneration"), ("paligemma", "PaliGemmaForConditionalGeneration"), ("pix2struct", "Pix2StructForConditionalGeneration"), ("qwen2_5_vl", "Qwen2_5_VLForConditionalGeneration"), ("qwen2_vl", "Qwen2VLForConditionalGeneration"), ("video_llava", "VideoLlavaForConditionalGeneration"), ("vipllava", "VipLlavaForConditionalGeneration"), ("vision-encoder-decoder", "VisionEncoderDecoderModel"), ] ) MODEL_FOR_RETRIEVAL_MAPPING_NAMES = OrderedDict( [ ("colpali", "ColPaliForRetrieval"), ] ) MODEL_FOR_IMAGE_TEXT_TO_TEXT_MAPPING_NAMES = OrderedDict( [ ("aria", "AriaForConditionalGeneration"), ("aya_vision", "AyaVisionForConditionalGeneration"), ("blip", "BlipForConditionalGeneration"), ("blip-2", "Blip2ForConditionalGeneration"), ("chameleon", "ChameleonForConditionalGeneration"), ("emu3", "Emu3ForConditionalGeneration"), ("fuyu", "FuyuForCausalLM"), ("gemma3", "Gemma3ForConditionalGeneration"), ("git", "GitForCausalLM"), ("got_ocr2", "GotOcr2ForConditionalGeneration"), ("idefics", "IdeficsForVisionText2Text"), ("idefics2", "Idefics2ForConditionalGeneration"), ("idefics3", "Idefics3ForConditionalGeneration"), ("instructblip", "InstructBlipForConditionalGeneration"), ("kosmos-2", "Kosmos2ForConditionalGeneration"), ("llama4", "Llama4ForConditionalGeneration"), ("llava", "LlavaForConditionalGeneration"), ("llava_next", "LlavaNextForConditionalGeneration"), ("llava_onevision", "LlavaOnevisionForConditionalGeneration"), ("mistral3", "Mistral3ForConditionalGeneration"), ("mllama", "MllamaForConditionalGeneration"), ("paligemma", "PaliGemmaForConditionalGeneration"), ("pix2struct", "Pix2StructForConditionalGeneration"), ("pixtral", "LlavaForConditionalGeneration"), ("qwen2_5_vl", "Qwen2_5_VLForConditionalGeneration"), ("qwen2_vl", "Qwen2VLForConditionalGeneration"), ("shieldgemma2", "Gemma3ForConditionalGeneration"), ("smolvlm", "SmolVLMForConditionalGeneration"), ("udop", "UdopForConditionalGeneration"), ("vipllava", "VipLlavaForConditionalGeneration"), ("vision-encoder-decoder", "VisionEncoderDecoderModel"), ] ) MODEL_FOR_MASKED_LM_MAPPING_NAMES = OrderedDict( [ # Model for Masked LM mapping ("albert", "AlbertForMaskedLM"), ("bart", "BartForConditionalGeneration"), ("bert", "BertForMaskedLM"), ("big_bird", "BigBirdForMaskedLM"), ("camembert", "CamembertForMaskedLM"), ("convbert", "ConvBertForMaskedLM"), ("data2vec-text", "Data2VecTextForMaskedLM"), ("deberta", "DebertaForMaskedLM"), ("deberta-v2", "DebertaV2ForMaskedLM"), ("distilbert", "DistilBertForMaskedLM"), ("electra", "ElectraForMaskedLM"), ("ernie", "ErnieForMaskedLM"), ("esm", "EsmForMaskedLM"), ("flaubert", "FlaubertWithLMHeadModel"), ("fnet", "FNetForMaskedLM"), ("funnel", "FunnelForMaskedLM"), ("ibert", "IBertForMaskedLM"), ("layoutlm", "LayoutLMForMaskedLM"), ("longformer", "LongformerForMaskedLM"), ("luke", "LukeForMaskedLM"), ("mbart", "MBartForConditionalGeneration"), ("mega", "MegaForMaskedLM"), ("megatron-bert", "MegatronBertForMaskedLM"), ("mobilebert", "MobileBertForMaskedLM"), ("modernbert", "ModernBertForMaskedLM"), ("mpnet", "MPNetForMaskedLM"), ("mra", "MraForMaskedLM"), ("mvp", "MvpForConditionalGeneration"), ("nezha", "NezhaForMaskedLM"), ("nystromformer", "NystromformerForMaskedLM"), ("perceiver", "PerceiverForMaskedLM"), ("qdqbert", "QDQBertForMaskedLM"), ("reformer", "ReformerForMaskedLM"), ("rembert", "RemBertForMaskedLM"), ("roberta", "RobertaForMaskedLM"), ("roberta-prelayernorm", "RobertaPreLayerNormForMaskedLM"), ("roc_bert", "RoCBertForMaskedLM"), ("roformer", "RoFormerForMaskedLM"), ("squeezebert", "SqueezeBertForMaskedLM"), ("tapas", "TapasForMaskedLM"), ("wav2vec2", "Wav2Vec2ForMaskedLM"), ("xlm", "XLMWithLMHeadModel"), ("xlm-roberta", "XLMRobertaForMaskedLM"), ("xlm-roberta-xl", "XLMRobertaXLForMaskedLM"), ("xmod", "XmodForMaskedLM"), ("yoso", "YosoForMaskedLM"), ] ) MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES = OrderedDict( [ # Model for Object Detection mapping ("conditional_detr", "ConditionalDetrForObjectDetection"), ("dab-detr", "DabDetrForObjectDetection"), ("deformable_detr", "DeformableDetrForObjectDetection"), ("deta", "DetaForObjectDetection"), ("detr", "DetrForObjectDetection"), ("rt_detr", "RTDetrForObjectDetection"), ("rt_detr_v2", "RTDetrV2ForObjectDetection"), ("table-transformer", "TableTransformerForObjectDetection"), ("yolos", "YolosForObjectDetection"), ] ) MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING_NAMES = OrderedDict( [ # Model for Zero Shot Object Detection mapping ("grounding-dino", "GroundingDinoForObjectDetection"), ("omdet-turbo", "OmDetTurboForObjectDetection"), ("owlv2", "Owlv2ForObjectDetection"), ("owlvit", "OwlViTForObjectDetection"), ] ) MODEL_FOR_DEPTH_ESTIMATION_MAPPING_NAMES = OrderedDict( [ # Model for depth estimation mapping ("depth_anything", "DepthAnythingForDepthEstimation"), ("depth_pro", "DepthProForDepthEstimation"), ("dpt", "DPTForDepthEstimation"), ("glpn", "GLPNForDepthEstimation"), ("prompt_depth_anything", "PromptDepthAnythingForDepthEstimation"), ("zoedepth", "ZoeDepthForDepthEstimation"), ] ) MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES = OrderedDict( [ # Model for Seq2Seq Causal LM mapping ("bart", "BartForConditionalGeneration"), ("bigbird_pegasus", "BigBirdPegasusForConditionalGeneration"), ("blenderbot", "BlenderbotForConditionalGeneration"), ("blenderbot-small", "BlenderbotSmallForConditionalGeneration"), ("encoder-decoder", "EncoderDecoderModel"), ("fsmt", "FSMTForConditionalGeneration"), ("gptsan-japanese", "GPTSanJapaneseForConditionalGeneration"), ("led", "LEDForConditionalGeneration"), ("longt5", "LongT5ForConditionalGeneration"), ("m2m_100", "M2M100ForConditionalGeneration"), ("marian", "MarianMTModel"), ("mbart", "MBartForConditionalGeneration"), ("mt5", "MT5ForConditionalGeneration"), ("mvp", "MvpForConditionalGeneration"), ("nllb-moe", "NllbMoeForConditionalGeneration"), ("pegasus", "PegasusForConditionalGeneration"), ("pegasus_x", "PegasusXForConditionalGeneration"), ("plbart", "PLBartForConditionalGeneration"), ("prophetnet", "ProphetNetForConditionalGeneration"), ("qwen2_audio", "Qwen2AudioForConditionalGeneration"), ("seamless_m4t", "SeamlessM4TForTextToText"), ("seamless_m4t_v2", "SeamlessM4Tv2ForTextToText"), ("switch_transformers", "SwitchTransformersForConditionalGeneration"), ("t5", "T5ForConditionalGeneration"), ("umt5", "UMT5ForConditionalGeneration"), ("xlm-prophetnet", "XLMProphetNetForConditionalGeneration"), ] ) MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES = OrderedDict( [ ("moonshine", "MoonshineForConditionalGeneration"), ("pop2piano", "Pop2PianoForConditionalGeneration"), ("seamless_m4t", "SeamlessM4TForSpeechToText"), ("seamless_m4t_v2", "SeamlessM4Tv2ForSpeechToText"), ("speech-encoder-decoder", "SpeechEncoderDecoderModel"), ("speech_to_text", "Speech2TextForConditionalGeneration"), ("speecht5", "SpeechT5ForSpeechToText"), ("whisper", "WhisperForConditionalGeneration"), ] ) MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES = OrderedDict( [ # Model for Sequence Classification mapping ("albert", "AlbertForSequenceClassification"), ("bart", "BartForSequenceClassification"), ("bert", "BertForSequenceClassification"), ("big_bird", "BigBirdForSequenceClassification"), ("bigbird_pegasus", "BigBirdPegasusForSequenceClassification"), ("biogpt", "BioGptForSequenceClassification"), ("bloom", "BloomForSequenceClassification"), ("camembert", "CamembertForSequenceClassification"), ("canine", "CanineForSequenceClassification"), ("code_llama", "LlamaForSequenceClassification"), ("convbert", "ConvBertForSequenceClassification"), ("ctrl", "CTRLForSequenceClassification"), ("data2vec-text", "Data2VecTextForSequenceClassification"), ("deberta", "DebertaForSequenceClassification"), ("deberta-v2", "DebertaV2ForSequenceClassification"), ("diffllama", "DiffLlamaForSequenceClassification"), ("distilbert", "DistilBertForSequenceClassification"), ("electra", "ElectraForSequenceClassification"), ("ernie", "ErnieForSequenceClassification"), ("ernie_m", "ErnieMForSequenceClassification"), ("esm", "EsmForSequenceClassification"), ("falcon", "FalconForSequenceClassification"), ("flaubert", "FlaubertForSequenceClassification"), ("fnet", "FNetForSequenceClassification"), ("funnel", "FunnelForSequenceClassification"), ("gemma", "GemmaForSequenceClassification"), ("gemma2", "Gemma2ForSequenceClassification"), ("glm", "GlmForSequenceClassification"), ("glm4", "Glm4ForSequenceClassification"), ("gpt-sw3", "GPT2ForSequenceClassification"), ("gpt2", "GPT2ForSequenceClassification"), ("gpt_bigcode", "GPTBigCodeForSequenceClassification"), ("gpt_neo", "GPTNeoForSequenceClassification"), ("gpt_neox", "GPTNeoXForSequenceClassification"), ("gptj", "GPTJForSequenceClassification"), ("helium", "HeliumForSequenceClassification"), ("ibert", "IBertForSequenceClassification"), ("jamba", "JambaForSequenceClassification"), ("jetmoe", "JetMoeForSequenceClassification"), ("layoutlm", "LayoutLMForSequenceClassification"), ("layoutlmv2", "LayoutLMv2ForSequenceClassification"), ("layoutlmv3", "LayoutLMv3ForSequenceClassification"), ("led", "LEDForSequenceClassification"), ("lilt", "LiltForSequenceClassification"), ("llama", "LlamaForSequenceClassification"), ("longformer", "LongformerForSequenceClassification"), ("luke", "LukeForSequenceClassification"), ("markuplm", "MarkupLMForSequenceClassification"), ("mbart", "MBartForSequenceClassification"), ("mega", "MegaForSequenceClassification"), ("megatron-bert", "MegatronBertForSequenceClassification"), ("mistral", "MistralForSequenceClassification"), ("mixtral", "MixtralForSequenceClassification"), ("mobilebert", "MobileBertForSequenceClassification"), ("modernbert", "ModernBertForSequenceClassification"), ("mpnet", "MPNetForSequenceClassification"), ("mpt", "MptForSequenceClassification"), ("mra", "MraForSequenceClassification"), ("mt5", "MT5ForSequenceClassification"), ("mvp", "MvpForSequenceClassification"), ("nemotron", "NemotronForSequenceClassification"), ("nezha", "NezhaForSequenceClassification"), ("nystromformer", "NystromformerForSequenceClassification"), ("open-llama", "OpenLlamaForSequenceClassification"), ("openai-gpt", "OpenAIGPTForSequenceClassification"), ("opt", "OPTForSequenceClassification"), ("perceiver", "PerceiverForSequenceClassification"), ("persimmon", "PersimmonForSequenceClassification"), ("phi", "PhiForSequenceClassification"), ("phi3", "Phi3ForSequenceClassification"), ("phimoe", "PhimoeForSequenceClassification"), ("plbart", "PLBartForSequenceClassification"), ("qdqbert", "QDQBertForSequenceClassification"), ("qwen2", "Qwen2ForSequenceClassification"), ("qwen2_moe", "Qwen2MoeForSequenceClassification"), ("qwen3", "Qwen3ForSequenceClassification"), ("qwen3_moe", "Qwen3MoeForSequenceClassification"), ("reformer", "ReformerForSequenceClassification"), ("rembert", "RemBertForSequenceClassification"), ("roberta", "RobertaForSequenceClassification"), ("roberta-prelayernorm", "RobertaPreLayerNormForSequenceClassification"), ("roc_bert", "RoCBertForSequenceClassification"), ("roformer", "RoFormerForSequenceClassification"), ("squeezebert", "SqueezeBertForSequenceClassification"), ("stablelm", "StableLmForSequenceClassification"), ("starcoder2", "Starcoder2ForSequenceClassification"), ("t5", "T5ForSequenceClassification"), ("tapas", "TapasForSequenceClassification"), ("transfo-xl", "TransfoXLForSequenceClassification"), ("umt5", "UMT5ForSequenceClassification"), ("xlm", "XLMForSequenceClassification"), ("xlm-roberta", "XLMRobertaForSequenceClassification"), ("xlm-roberta-xl", "XLMRobertaXLForSequenceClassification"), ("xlnet", "XLNetForSequenceClassification"), ("xmod", "XmodForSequenceClassification"), ("yoso", "YosoForSequenceClassification"), ("zamba", "ZambaForSequenceClassification"), ("zamba2", "Zamba2ForSequenceClassification"), ] ) MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES = OrderedDict( [ # Model for Question Answering mapping ("albert", "AlbertForQuestionAnswering"), ("bart", "BartForQuestionAnswering"), ("bert", "BertForQuestionAnswering"), ("big_bird", "BigBirdForQuestionAnswering"), ("bigbird_pegasus", "BigBirdPegasusForQuestionAnswering"), ("bloom", "BloomForQuestionAnswering"), ("camembert", "CamembertForQuestionAnswering"), ("canine", "CanineForQuestionAnswering"), ("convbert", "ConvBertForQuestionAnswering"), ("data2vec-text", "Data2VecTextForQuestionAnswering"), ("deberta", "DebertaForQuestionAnswering"), ("deberta-v2", "DebertaV2ForQuestionAnswering"), ("diffllama", "DiffLlamaForQuestionAnswering"), ("distilbert", "DistilBertForQuestionAnswering"), ("electra", "ElectraForQuestionAnswering"), ("ernie", "ErnieForQuestionAnswering"), ("ernie_m", "ErnieMForQuestionAnswering"), ("falcon", "FalconForQuestionAnswering"), ("flaubert", "FlaubertForQuestionAnsweringSimple"), ("fnet", "FNetForQuestionAnswering"), ("funnel", "FunnelForQuestionAnswering"), ("gpt2", "GPT2ForQuestionAnswering"), ("gpt_neo", "GPTNeoForQuestionAnswering"), ("gpt_neox", "GPTNeoXForQuestionAnswering"), ("gptj", "GPTJForQuestionAnswering"), ("ibert", "IBertForQuestionAnswering"), ("layoutlmv2", "LayoutLMv2ForQuestionAnswering"), ("layoutlmv3", "LayoutLMv3ForQuestionAnswering"), ("led", "LEDForQuestionAnswering"), ("lilt", "LiltForQuestionAnswering"), ("llama", "LlamaForQuestionAnswering"), ("longformer", "LongformerForQuestionAnswering"), ("luke", "LukeForQuestionAnswering"), ("lxmert", "LxmertForQuestionAnswering"), ("markuplm", "MarkupLMForQuestionAnswering"), ("mbart", "MBartForQuestionAnswering"), ("mega", "MegaForQuestionAnswering"), ("megatron-bert", "MegatronBertForQuestionAnswering"), ("mistral", "MistralForQuestionAnswering"), ("mixtral", "MixtralForQuestionAnswering"), ("mobilebert", "MobileBertForQuestionAnswering"), ("modernbert", "ModernBertForQuestionAnswering"), ("mpnet", "MPNetForQuestionAnswering"), ("mpt", "MptForQuestionAnswering"), ("mra", "MraForQuestionAnswering"), ("mt5", "MT5ForQuestionAnswering"), ("mvp", "MvpForQuestionAnswering"), ("nemotron", "NemotronForQuestionAnswering"), ("nezha", "NezhaForQuestionAnswering"), ("nystromformer", "NystromformerForQuestionAnswering"), ("opt", "OPTForQuestionAnswering"), ("qdqbert", "QDQBertForQuestionAnswering"), ("qwen2", "Qwen2ForQuestionAnswering"), ("qwen2_moe", "Qwen2MoeForQuestionAnswering"), ("qwen3", "Qwen3ForQuestionAnswering"), ("qwen3_moe", "Qwen3MoeForQuestionAnswering"), ("reformer", "ReformerForQuestionAnswering"), ("rembert", "RemBertForQuestionAnswering"), ("roberta", "RobertaForQuestionAnswering"), ("roberta-prelayernorm", "RobertaPreLayerNormForQuestionAnswering"), ("roc_bert", "RoCBertForQuestionAnswering"), ("roformer", "RoFormerForQuestionAnswering"), ("splinter", "SplinterForQuestionAnswering"), ("squeezebert", "SqueezeBertForQuestionAnswering"), ("t5", "T5ForQuestionAnswering"), ("umt5", "UMT5ForQuestionAnswering"), ("xlm", "XLMForQuestionAnsweringSimple"), ("xlm-roberta", "XLMRobertaForQuestionAnswering"), ("xlm-roberta-xl", "XLMRobertaXLForQuestionAnswering"), ("xlnet", "XLNetForQuestionAnsweringSimple"), ("xmod", "XmodForQuestionAnswering"), ("yoso", "YosoForQuestionAnswering"), ] ) MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING_NAMES = OrderedDict( [ # Model for Table Question Answering mapping ("tapas", "TapasForQuestionAnswering"), ] ) MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING_NAMES = OrderedDict( [ ("blip", "BlipForQuestionAnswering"), ("blip-2", "Blip2ForConditionalGeneration"), ("vilt", "ViltForQuestionAnswering"), ] ) MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING_NAMES = OrderedDict( [ ("layoutlm", "LayoutLMForQuestionAnswering"), ("layoutlmv2", "LayoutLMv2ForQuestionAnswering"), ("layoutlmv3", "LayoutLMv3ForQuestionAnswering"), ] ) MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES = OrderedDict( [ # Model for Token Classification mapping ("albert", "AlbertForTokenClassification"), ("bert", "BertForTokenClassification"), ("big_bird", "BigBirdForTokenClassification"), ("biogpt", "BioGptForTokenClassification"), ("bloom", "BloomForTokenClassification"), ("bros", "BrosForTokenClassification"), ("camembert", "CamembertForTokenClassification"), ("canine", "CanineForTokenClassification"), ("convbert", "ConvBertForTokenClassification"), ("data2vec-text", "Data2VecTextForTokenClassification"), ("deberta", "DebertaForTokenClassification"), ("deberta-v2", "DebertaV2ForTokenClassification"), ("diffllama", "DiffLlamaForTokenClassification"), ("distilbert", "DistilBertForTokenClassification"), ("electra", "ElectraForTokenClassification"), ("ernie", "ErnieForTokenClassification"), ("ernie_m", "ErnieMForTokenClassification"), ("esm", "EsmForTokenClassification"), ("falcon", "FalconForTokenClassification"), ("flaubert", "FlaubertForTokenClassification"), ("fnet", "FNetForTokenClassification"), ("funnel", "FunnelForTokenClassification"), ("gemma", "GemmaForTokenClassification"), ("gemma2", "Gemma2ForTokenClassification"), ("glm", "GlmForTokenClassification"), ("glm4", "Glm4ForTokenClassification"), ("gpt-sw3", "GPT2ForTokenClassification"), ("gpt2", "GPT2ForTokenClassification"), ("gpt_bigcode", "GPTBigCodeForTokenClassification"), ("gpt_neo", "GPTNeoForTokenClassification"), ("gpt_neox", "GPTNeoXForTokenClassification"), ("helium", "HeliumForTokenClassification"), ("ibert", "IBertForTokenClassification"), ("layoutlm", "LayoutLMForTokenClassification"), ("layoutlmv2", "LayoutLMv2ForTokenClassification"), ("layoutlmv3", "LayoutLMv3ForTokenClassification"), ("lilt", "LiltForTokenClassification"), ("llama", "LlamaForTokenClassification"), ("longformer", "LongformerForTokenClassification"), ("luke", "LukeForTokenClassification"), ("markuplm", "MarkupLMForTokenClassification"), ("mega", "MegaForTokenClassification"), ("megatron-bert", "MegatronBertForTokenClassification"), ("mistral", "MistralForTokenClassification"), ("mixtral", "MixtralForTokenClassification"), ("mobilebert", "MobileBertForTokenClassification"), ("modernbert", "ModernBertForTokenClassification"), ("mpnet", "MPNetForTokenClassification"), ("mpt", "MptForTokenClassification"), ("mra", "MraForTokenClassification"), ("mt5", "MT5ForTokenClassification"), ("nemotron", "NemotronForTokenClassification"), ("nezha", "NezhaForTokenClassification"), ("nystromformer", "NystromformerForTokenClassification"), ("persimmon", "PersimmonForTokenClassification"), ("phi", "PhiForTokenClassification"), ("phi3", "Phi3ForTokenClassification"), ("qdqbert", "QDQBertForTokenClassification"), ("qwen2", "Qwen2ForTokenClassification"), ("qwen2_moe", "Qwen2MoeForTokenClassification"), ("qwen3", "Qwen3ForTokenClassification"), ("qwen3_moe", "Qwen3MoeForTokenClassification"), ("rembert", "RemBertForTokenClassification"), ("roberta", "RobertaForTokenClassification"), ("roberta-prelayernorm", "RobertaPreLayerNormForTokenClassification"), ("roc_bert", "RoCBertForTokenClassification"), ("roformer", "RoFormerForTokenClassification"), ("squeezebert", "SqueezeBertForTokenClassification"), ("stablelm", "StableLmForTokenClassification"), ("starcoder2", "Starcoder2ForTokenClassification"), ("t5", "T5ForTokenClassification"), ("umt5", "UMT5ForTokenClassification"), ("xlm", "XLMForTokenClassification"), ("xlm-roberta", "XLMRobertaForTokenClassification"), ("xlm-roberta-xl", "XLMRobertaXLForTokenClassification"), ("xlnet", "XLNetForTokenClassification"), ("xmod", "XmodForTokenClassification"), ("yoso", "YosoForTokenClassification"), ] ) MODEL_FOR_MULTIPLE_CHOICE_MAPPING_NAMES = OrderedDict( [ # Model for Multiple Choice mapping ("albert", "AlbertForMultipleChoice"), ("bert", "BertForMultipleChoice"), ("big_bird", "BigBirdForMultipleChoice"), ("camembert", "CamembertForMultipleChoice"), ("canine", "CanineForMultipleChoice"), ("convbert", "ConvBertForMultipleChoice"), ("data2vec-text", "Data2VecTextForMultipleChoice"), ("deberta-v2", "DebertaV2ForMultipleChoice"), ("distilbert", "DistilBertForMultipleChoice"), ("electra", "ElectraForMultipleChoice"), ("ernie", "ErnieForMultipleChoice"), ("ernie_m", "ErnieMForMultipleChoice"), ("flaubert", "FlaubertForMultipleChoice"), ("fnet", "FNetForMultipleChoice"), ("funnel", "FunnelForMultipleChoice"), ("ibert", "IBertForMultipleChoice"), ("longformer", "LongformerForMultipleChoice"), ("luke", "LukeForMultipleChoice"), ("mega", "MegaForMultipleChoice"), ("megatron-bert", "MegatronBertForMultipleChoice"), ("mobilebert", "MobileBertForMultipleChoice"), ("mpnet", "MPNetForMultipleChoice"), ("mra", "MraForMultipleChoice"), ("nezha", "NezhaForMultipleChoice"), ("nystromformer", "NystromformerForMultipleChoice"), ("qdqbert", "QDQBertForMultipleChoice"), ("rembert", "RemBertForMultipleChoice"), ("roberta", "RobertaForMultipleChoice"), ("roberta-prelayernorm", "RobertaPreLayerNormForMultipleChoice"), ("roc_bert", "RoCBertForMultipleChoice"), ("roformer", "RoFormerForMultipleChoice"), ("squeezebert", "SqueezeBertForMultipleChoice"), ("xlm", "XLMForMultipleChoice"), ("xlm-roberta", "XLMRobertaForMultipleChoice"), ("xlm-roberta-xl", "XLMRobertaXLForMultipleChoice"), ("xlnet", "XLNetForMultipleChoice"), ("xmod", "XmodForMultipleChoice"), ("yoso", "YosoForMultipleChoice"), ] ) MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING_NAMES = OrderedDict( [ ("bert", "BertForNextSentencePrediction"), ("ernie", "ErnieForNextSentencePrediction"), ("fnet", "FNetForNextSentencePrediction"), ("megatron-bert", "MegatronBertForNextSentencePrediction"), ("mobilebert", "MobileBertForNextSentencePrediction"), ("nezha", "NezhaForNextSentencePrediction"), ("qdqbert", "QDQBertForNextSentencePrediction"), ] ) MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES = OrderedDict( [ # Model for Audio Classification mapping ("audio-spectrogram-transformer", "ASTForAudioClassification"), ("data2vec-audio", "Data2VecAudioForSequenceClassification"), ("hubert", "HubertForSequenceClassification"), ("sew", "SEWForSequenceClassification"), ("sew-d", "SEWDForSequenceClassification"), ("unispeech", "UniSpeechForSequenceClassification"), ("unispeech-sat", "UniSpeechSatForSequenceClassification"), ("wav2vec2", "Wav2Vec2ForSequenceClassification"), ("wav2vec2-bert", "Wav2Vec2BertForSequenceClassification"), ("wav2vec2-conformer", "Wav2Vec2ConformerForSequenceClassification"), ("wavlm", "WavLMForSequenceClassification"), ("whisper", "WhisperForAudioClassification"), ] ) MODEL_FOR_CTC_MAPPING_NAMES = OrderedDict( [ # Model for Connectionist temporal classification (CTC) mapping ("data2vec-audio", "Data2VecAudioForCTC"), ("hubert", "HubertForCTC"), ("mctct", "MCTCTForCTC"), ("sew", "SEWForCTC"), ("sew-d", "SEWDForCTC"), ("unispeech", "UniSpeechForCTC"), ("unispeech-sat", "UniSpeechSatForCTC"), ("wav2vec2", "Wav2Vec2ForCTC"), ("wav2vec2-bert", "Wav2Vec2BertForCTC"), ("wav2vec2-conformer", "Wav2Vec2ConformerForCTC"), ("wavlm", "WavLMForCTC"), ] ) MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING_NAMES = OrderedDict( [ # Model for Audio Classification mapping ("data2vec-audio", "Data2VecAudioForAudioFrameClassification"), ("unispeech-sat", "UniSpeechSatForAudioFrameClassification"), ("wav2vec2", "Wav2Vec2ForAudioFrameClassification"), ("wav2vec2-bert", "Wav2Vec2BertForAudioFrameClassification"), ("wav2vec2-conformer", "Wav2Vec2ConformerForAudioFrameClassification"), ("wavlm", "WavLMForAudioFrameClassification"), ] ) MODEL_FOR_AUDIO_XVECTOR_MAPPING_NAMES = OrderedDict( [ # Model for Audio Classification mapping ("data2vec-audio", "Data2VecAudioForXVector"), ("unispeech-sat", "UniSpeechSatForXVector"), ("wav2vec2", "Wav2Vec2ForXVector"), ("wav2vec2-bert", "Wav2Vec2BertForXVector"), ("wav2vec2-conformer", "Wav2Vec2ConformerForXVector"), ("wavlm", "WavLMForXVector"), ] ) MODEL_FOR_TEXT_TO_SPECTROGRAM_MAPPING_NAMES = OrderedDict( [ # Model for Text-To-Spectrogram mapping ("fastspeech2_conformer", "FastSpeech2ConformerModel"), ("speecht5", "SpeechT5ForTextToSpeech"), ] ) MODEL_FOR_TEXT_TO_WAVEFORM_MAPPING_NAMES = OrderedDict( [ # Model for Text-To-Waveform mapping ("bark", "BarkModel"), ("fastspeech2_conformer", "FastSpeech2ConformerWithHifiGan"), ("musicgen", "MusicgenForConditionalGeneration"), ("musicgen_melody", "MusicgenMelodyForConditionalGeneration"), ("seamless_m4t", "SeamlessM4TForTextToSpeech"), ("seamless_m4t_v2", "SeamlessM4Tv2ForTextToSpeech"), ("vits", "VitsModel"), ] ) MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING_NAMES = OrderedDict( [ # Model for Zero Shot Image Classification mapping ("align", "AlignModel"), ("altclip", "AltCLIPModel"), ("blip", "BlipModel"), ("blip-2", "Blip2ForImageTextRetrieval"), ("chinese_clip", "ChineseCLIPModel"), ("clip", "CLIPModel"), ("clipseg", "CLIPSegModel"), ("siglip", "SiglipModel"), ("siglip2", "Siglip2Model"), ] ) MODEL_FOR_BACKBONE_MAPPING_NAMES = OrderedDict( [ # Backbone mapping ("beit", "BeitBackbone"), ("bit", "BitBackbone"), ("convnext", "ConvNextBackbone"), ("convnextv2", "ConvNextV2Backbone"), ("dinat", "DinatBackbone"), ("dinov2", "Dinov2Backbone"), ("dinov2_with_registers", "Dinov2WithRegistersBackbone"), ("focalnet", "FocalNetBackbone"), ("hiera", "HieraBackbone"), ("maskformer-swin", "MaskFormerSwinBackbone"), ("nat", "NatBackbone"), ("pvt_v2", "PvtV2Backbone"), ("resnet", "ResNetBackbone"), ("rt_detr_resnet", "RTDetrResNetBackbone"), ("swin", "SwinBackbone"), ("swinv2", "Swinv2Backbone"), ("textnet", "TextNetBackbone"), ("timm_backbone", "TimmBackbone"), ("vitdet", "VitDetBackbone"), ("vitpose_backbone", "VitPoseBackbone"), ] ) MODEL_FOR_MASK_GENERATION_MAPPING_NAMES = OrderedDict( [ ("sam", "SamModel"), ] ) MODEL_FOR_KEYPOINT_DETECTION_MAPPING_NAMES = OrderedDict( [ ("superpoint", "SuperPointForKeypointDetection"), ] ) MODEL_FOR_TEXT_ENCODING_MAPPING_NAMES = OrderedDict( [ ("albert", "AlbertModel"), ("bert", "BertModel"), ("big_bird", "BigBirdModel"), ("clip_text_model", "CLIPTextModel"), ("data2vec-text", "Data2VecTextModel"), ("deberta", "DebertaModel"), ("deberta-v2", "DebertaV2Model"), ("distilbert", "DistilBertModel"), ("electra", "ElectraModel"), ("emu3", "Emu3TextModel"), ("flaubert", "FlaubertModel"), ("ibert", "IBertModel"), ("llama4", "Llama4TextModel"), ("longformer", "LongformerModel"), ("mllama", "MllamaTextModel"), ("mobilebert", "MobileBertModel"), ("mt5", "MT5EncoderModel"), ("nystromformer", "NystromformerModel"), ("reformer", "ReformerModel"), ("rembert", "RemBertModel"), ("roberta", "RobertaModel"), ("roberta-prelayernorm", "RobertaPreLayerNormModel"), ("roc_bert", "RoCBertModel"), ("roformer", "RoFormerModel"), ("squeezebert", "SqueezeBertModel"), ("t5", "T5EncoderModel"), ("umt5", "UMT5EncoderModel"), ("xlm", "XLMModel"), ("xlm-roberta", "XLMRobertaModel"), ("xlm-roberta-xl", "XLMRobertaXLModel"), ] ) MODEL_FOR_TIME_SERIES_CLASSIFICATION_MAPPING_NAMES = OrderedDict( [ ("patchtsmixer", "PatchTSMixerForTimeSeriesClassification"), ("patchtst", "PatchTSTForClassification"), ] ) MODEL_FOR_TIME_SERIES_REGRESSION_MAPPING_NAMES = OrderedDict( [ ("patchtsmixer", "PatchTSMixerForRegression"), ("patchtst", "PatchTSTForRegression"), ] ) MODEL_FOR_IMAGE_TO_IMAGE_MAPPING_NAMES = OrderedDict( [ ("swin2sr", "Swin2SRForImageSuperResolution"), ] ) MODEL_MAPPING = _LazyAutoMapping(CONFIG_MAPPING_NAMES, MODEL_MAPPING_NAMES) MODEL_FOR_PRETRAINING_MAPPING = _LazyAutoMapping(CONFIG_MAPPING_NAMES, MODEL_FOR_PRETRAINING_MAPPING_NAMES) MODEL_WITH_LM_HEAD_MAPPING = _LazyAutoMapping(CONFIG_MAPPING_NAMES, MODEL_WITH_LM_HEAD_MAPPING_NAMES) MODEL_FOR_CAUSAL_LM_MAPPING = _LazyAutoMapping(CONFIG_MAPPING_NAMES, MODEL_FOR_CAUSAL_LM_MAPPING_NAMES) MODEL_FOR_CAUSAL_IMAGE_MODELING_MAPPING = _LazyAutoMapping( CONFIG_MAPPING_NAMES, MODEL_FOR_CAUSAL_IMAGE_MODELING_MAPPING_NAMES ) MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING = _LazyAutoMapping( CONFIG_MAPPING_NAMES, MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES ) MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING = _LazyAutoMapping( CONFIG_MAPPING_NAMES, MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING_NAMES ) MODEL_FOR_IMAGE_SEGMENTATION_MAPPING = _LazyAutoMapping( CONFIG_MAPPING_NAMES, MODEL_FOR_IMAGE_SEGMENTATION_MAPPING_NAMES ) MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING = _LazyAutoMapping( CONFIG_MAPPING_NAMES, MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING_NAMES ) MODEL_FOR_INSTANCE_SEGMENTATION_MAPPING = _LazyAutoMapping( CONFIG_MAPPING_NAMES, MODEL_FOR_INSTANCE_SEGMENTATION_MAPPING_NAMES ) MODEL_FOR_UNIVERSAL_SEGMENTATION_MAPPING = _LazyAutoMapping( CONFIG_MAPPING_NAMES, MODEL_FOR_UNIVERSAL_SEGMENTATION_MAPPING_NAMES ) MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING = _LazyAutoMapping( CONFIG_MAPPING_NAMES, MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING_NAMES ) MODEL_FOR_VISION_2_SEQ_MAPPING = _LazyAutoMapping(CONFIG_MAPPING_NAMES, MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES) MODEL_FOR_IMAGE_TEXT_TO_TEXT_MAPPING = _LazyAutoMapping( CONFIG_MAPPING_NAMES, MODEL_FOR_IMAGE_TEXT_TO_TEXT_MAPPING_NAMES ) MODEL_FOR_RETRIEVAL_MAPPING = _LazyAutoMapping(CONFIG_MAPPING_NAMES, MODEL_FOR_RETRIEVAL_MAPPING_NAMES) MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING = _LazyAutoMapping( CONFIG_MAPPING_NAMES, MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING_NAMES ) MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING = _LazyAutoMapping( CONFIG_MAPPING_NAMES, MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING_NAMES ) MODEL_FOR_MASKED_LM_MAPPING = _LazyAutoMapping(CONFIG_MAPPING_NAMES, MODEL_FOR_MASKED_LM_MAPPING_NAMES) MODEL_FOR_IMAGE_MAPPING = _LazyAutoMapping(CONFIG_MAPPING_NAMES, MODEL_FOR_IMAGE_MAPPING_NAMES) MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING = _LazyAutoMapping( CONFIG_MAPPING_NAMES, MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING_NAMES ) MODEL_FOR_OBJECT_DETECTION_MAPPING = _LazyAutoMapping(CONFIG_MAPPING_NAMES, MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES) MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING = _LazyAutoMapping( CONFIG_MAPPING_NAMES, MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING_NAMES ) MODEL_FOR_DEPTH_ESTIMATION_MAPPING = _LazyAutoMapping(CONFIG_MAPPING_NAMES, MODEL_FOR_DEPTH_ESTIMATION_MAPPING_NAMES) MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING = _LazyAutoMapping( CONFIG_MAPPING_NAMES, MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES ) MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING = _LazyAutoMapping( CONFIG_MAPPING_NAMES, MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES ) MODEL_FOR_QUESTION_ANSWERING_MAPPING = _LazyAutoMapping( CONFIG_MAPPING_NAMES, MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES ) MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING = _LazyAutoMapping( CONFIG_MAPPING_NAMES, MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING_NAMES ) MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING = _LazyAutoMapping( CONFIG_MAPPING_NAMES, MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES ) MODEL_FOR_MULTIPLE_CHOICE_MAPPING = _LazyAutoMapping(CONFIG_MAPPING_NAMES, MODEL_FOR_MULTIPLE_CHOICE_MAPPING_NAMES) MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING = _LazyAutoMapping( CONFIG_MAPPING_NAMES, MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING_NAMES ) MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING = _LazyAutoMapping( CONFIG_MAPPING_NAMES, MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES ) MODEL_FOR_CTC_MAPPING = _LazyAutoMapping(CONFIG_MAPPING_NAMES, MODEL_FOR_CTC_MAPPING_NAMES) MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING = _LazyAutoMapping(CONFIG_MAPPING_NAMES, MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES) MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING = _LazyAutoMapping( CONFIG_MAPPING_NAMES, MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING_NAMES ) MODEL_FOR_AUDIO_XVECTOR_MAPPING = _LazyAutoMapping(CONFIG_MAPPING_NAMES, MODEL_FOR_AUDIO_XVECTOR_MAPPING_NAMES) MODEL_FOR_TEXT_TO_SPECTROGRAM_MAPPING = _LazyAutoMapping( CONFIG_MAPPING_NAMES, MODEL_FOR_TEXT_TO_SPECTROGRAM_MAPPING_NAMES ) MODEL_FOR_TEXT_TO_WAVEFORM_MAPPING = _LazyAutoMapping(CONFIG_MAPPING_NAMES, MODEL_FOR_TEXT_TO_WAVEFORM_MAPPING_NAMES) MODEL_FOR_BACKBONE_MAPPING = _LazyAutoMapping(CONFIG_MAPPING_NAMES, MODEL_FOR_BACKBONE_MAPPING_NAMES) MODEL_FOR_MASK_GENERATION_MAPPING = _LazyAutoMapping(CONFIG_MAPPING_NAMES, MODEL_FOR_MASK_GENERATION_MAPPING_NAMES) MODEL_FOR_KEYPOINT_DETECTION_MAPPING = _LazyAutoMapping( CONFIG_MAPPING_NAMES, MODEL_FOR_KEYPOINT_DETECTION_MAPPING_NAMES ) MODEL_FOR_TEXT_ENCODING_MAPPING = _LazyAutoMapping(CONFIG_MAPPING_NAMES, MODEL_FOR_TEXT_ENCODING_MAPPING_NAMES) MODEL_FOR_TIME_SERIES_CLASSIFICATION_MAPPING = _LazyAutoMapping( CONFIG_MAPPING_NAMES, MODEL_FOR_TIME_SERIES_CLASSIFICATION_MAPPING_NAMES ) MODEL_FOR_TIME_SERIES_REGRESSION_MAPPING = _LazyAutoMapping( CONFIG_MAPPING_NAMES, MODEL_FOR_TIME_SERIES_REGRESSION_MAPPING_NAMES ) MODEL_FOR_IMAGE_TO_IMAGE_MAPPING = _LazyAutoMapping(CONFIG_MAPPING_NAMES, MODEL_FOR_IMAGE_TO_IMAGE_MAPPING_NAMES) class AutoModelForMaskGeneration(_BaseAutoModelClass): _model_mapping = MODEL_FOR_MASK_GENERATION_MAPPING class AutoModelForKeypointDetection(_BaseAutoModelClass): _model_mapping = MODEL_FOR_KEYPOINT_DETECTION_MAPPING class AutoModelForTextEncoding(_BaseAutoModelClass): _model_mapping = MODEL_FOR_TEXT_ENCODING_MAPPING class AutoModelForImageToImage(_BaseAutoModelClass): _model_mapping = MODEL_FOR_IMAGE_TO_IMAGE_MAPPING class AutoModel(_BaseAutoModelClass): _model_mapping = MODEL_MAPPING AutoModel = auto_class_update(AutoModel) class AutoModelForPreTraining(_BaseAutoModelClass): _model_mapping = MODEL_FOR_PRETRAINING_MAPPING AutoModelForPreTraining = auto_class_update(AutoModelForPreTraining, head_doc="pretraining") # Private on purpose, the public class will add the deprecation warnings. class _AutoModelWithLMHead(_BaseAutoModelClass): _model_mapping = MODEL_WITH_LM_HEAD_MAPPING _AutoModelWithLMHead = auto_class_update(_AutoModelWithLMHead, head_doc="language modeling") class AutoModelForCausalLM(_BaseAutoModelClass): _model_mapping = MODEL_FOR_CAUSAL_LM_MAPPING AutoModelForCausalLM = auto_class_update(AutoModelForCausalLM, head_doc="causal language modeling") class AutoModelForMaskedLM(_BaseAutoModelClass): _model_mapping = MODEL_FOR_MASKED_LM_MAPPING AutoModelForMaskedLM = auto_class_update(AutoModelForMaskedLM, head_doc="masked language modeling") class AutoModelForSeq2SeqLM(_BaseAutoModelClass): _model_mapping = MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING AutoModelForSeq2SeqLM = auto_class_update( AutoModelForSeq2SeqLM, head_doc="sequence-to-sequence language modeling", checkpoint_for_example="google-t5/t5-base", ) class AutoModelForSequenceClassification(_BaseAutoModelClass): _model_mapping = MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING AutoModelForSequenceClassification = auto_class_update( AutoModelForSequenceClassification, head_doc="sequence classification" ) class AutoModelForQuestionAnswering(_BaseAutoModelClass): _model_mapping = MODEL_FOR_QUESTION_ANSWERING_MAPPING AutoModelForQuestionAnswering = auto_class_update(AutoModelForQuestionAnswering, head_doc="question answering") class AutoModelForTableQuestionAnswering(_BaseAutoModelClass): _model_mapping = MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING AutoModelForTableQuestionAnswering = auto_class_update( AutoModelForTableQuestionAnswering, head_doc="table question answering", checkpoint_for_example="google/tapas-base-finetuned-wtq", ) class AutoModelForVisualQuestionAnswering(_BaseAutoModelClass): _model_mapping = MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING AutoModelForVisualQuestionAnswering = auto_class_update( AutoModelForVisualQuestionAnswering, head_doc="visual question answering", checkpoint_for_example="dandelin/vilt-b32-finetuned-vqa", ) class AutoModelForDocumentQuestionAnswering(_BaseAutoModelClass): _model_mapping = MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING AutoModelForDocumentQuestionAnswering = auto_class_update( AutoModelForDocumentQuestionAnswering, head_doc="document question answering", checkpoint_for_example='impira/layoutlm-document-qa", revision="52e01b3', ) class AutoModelForTokenClassification(_BaseAutoModelClass): _model_mapping = MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING AutoModelForTokenClassification = auto_class_update(AutoModelForTokenClassification, head_doc="token classification") class AutoModelForMultipleChoice(_BaseAutoModelClass): _model_mapping = MODEL_FOR_MULTIPLE_CHOICE_MAPPING AutoModelForMultipleChoice = auto_class_update(AutoModelForMultipleChoice, head_doc="multiple choice") class AutoModelForNextSentencePrediction(_BaseAutoModelClass): _model_mapping = MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING AutoModelForNextSentencePrediction = auto_class_update( AutoModelForNextSentencePrediction, head_doc="next sentence prediction" ) class AutoModelForImageClassification(_BaseAutoModelClass): _model_mapping = MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING AutoModelForImageClassification = auto_class_update(AutoModelForImageClassification, head_doc="image classification") class AutoModelForZeroShotImageClassification(_BaseAutoModelClass): _model_mapping = MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING AutoModelForZeroShotImageClassification = auto_class_update( AutoModelForZeroShotImageClassification, head_doc="zero-shot image classification" ) class AutoModelForImageSegmentation(_BaseAutoModelClass): _model_mapping = MODEL_FOR_IMAGE_SEGMENTATION_MAPPING AutoModelForImageSegmentation = auto_class_update(AutoModelForImageSegmentation, head_doc="image segmentation") class AutoModelForSemanticSegmentation(_BaseAutoModelClass): _model_mapping = MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING AutoModelForSemanticSegmentation = auto_class_update( AutoModelForSemanticSegmentation, head_doc="semantic segmentation" ) class AutoModelForUniversalSegmentation(_BaseAutoModelClass): _model_mapping = MODEL_FOR_UNIVERSAL_SEGMENTATION_MAPPING AutoModelForUniversalSegmentation = auto_class_update( AutoModelForUniversalSegmentation, head_doc="universal image segmentation" ) class AutoModelForInstanceSegmentation(_BaseAutoModelClass): _model_mapping = MODEL_FOR_INSTANCE_SEGMENTATION_MAPPING AutoModelForInstanceSegmentation = auto_class_update( AutoModelForInstanceSegmentation, head_doc="instance segmentation" ) class AutoModelForObjectDetection(_BaseAutoModelClass): _model_mapping = MODEL_FOR_OBJECT_DETECTION_MAPPING AutoModelForObjectDetection = auto_class_update(AutoModelForObjectDetection, head_doc="object detection") class AutoModelForZeroShotObjectDetection(_BaseAutoModelClass): _model_mapping = MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING AutoModelForZeroShotObjectDetection = auto_class_update( AutoModelForZeroShotObjectDetection, head_doc="zero-shot object detection" ) class AutoModelForDepthEstimation(_BaseAutoModelClass): _model_mapping = MODEL_FOR_DEPTH_ESTIMATION_MAPPING AutoModelForDepthEstimation = auto_class_update(AutoModelForDepthEstimation, head_doc="depth estimation") class AutoModelForVideoClassification(_BaseAutoModelClass): _model_mapping = MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING AutoModelForVideoClassification = auto_class_update(AutoModelForVideoClassification, head_doc="video classification") class AutoModelForVision2Seq(_BaseAutoModelClass): _model_mapping = MODEL_FOR_VISION_2_SEQ_MAPPING AutoModelForVision2Seq = auto_class_update(AutoModelForVision2Seq, head_doc="vision-to-text modeling") class AutoModelForImageTextToText(_BaseAutoModelClass): _model_mapping = MODEL_FOR_IMAGE_TEXT_TO_TEXT_MAPPING AutoModelForImageTextToText = auto_class_update(AutoModelForImageTextToText, head_doc="image-text-to-text modeling") class AutoModelForAudioClassification(_BaseAutoModelClass): _model_mapping = MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING AutoModelForAudioClassification = auto_class_update(AutoModelForAudioClassification, head_doc="audio classification") class AutoModelForCTC(_BaseAutoModelClass): _model_mapping = MODEL_FOR_CTC_MAPPING AutoModelForCTC = auto_class_update(AutoModelForCTC, head_doc="connectionist temporal classification") class AutoModelForSpeechSeq2Seq(_BaseAutoModelClass): _model_mapping = MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING AutoModelForSpeechSeq2Seq = auto_class_update( AutoModelForSpeechSeq2Seq, head_doc="sequence-to-sequence speech-to-text modeling" ) class AutoModelForAudioFrameClassification(_BaseAutoModelClass): _model_mapping = MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING AutoModelForAudioFrameClassification = auto_class_update( AutoModelForAudioFrameClassification, head_doc="audio frame (token) classification" ) class AutoModelForAudioXVector(_BaseAutoModelClass): _model_mapping = MODEL_FOR_AUDIO_XVECTOR_MAPPING class AutoModelForTextToSpectrogram(_BaseAutoModelClass): _model_mapping = MODEL_FOR_TEXT_TO_SPECTROGRAM_MAPPING class AutoModelForTextToWaveform(_BaseAutoModelClass): _model_mapping = MODEL_FOR_TEXT_TO_WAVEFORM_MAPPING class AutoBackbone(_BaseAutoBackboneClass): _model_mapping = MODEL_FOR_BACKBONE_MAPPING AutoModelForAudioXVector = auto_class_update(AutoModelForAudioXVector, head_doc="audio retrieval via x-vector") class AutoModelForMaskedImageModeling(_BaseAutoModelClass): _model_mapping = MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING AutoModelForMaskedImageModeling = auto_class_update(AutoModelForMaskedImageModeling, head_doc="masked image modeling") class AutoModelWithLMHead(_AutoModelWithLMHead): @classmethod def from_config(cls, config): warnings.warn( "The class `AutoModelWithLMHead` is deprecated and will be removed in a future version. Please use " "`AutoModelForCausalLM` for causal language models, `AutoModelForMaskedLM` for masked language models and " "`AutoModelForSeq2SeqLM` for encoder-decoder models.", FutureWarning, ) return super().from_config(config) @classmethod def from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs): warnings.warn( "The class `AutoModelWithLMHead` is deprecated and will be removed in a future version. Please use " "`AutoModelForCausalLM` for causal language models, `AutoModelForMaskedLM` for masked language models and " "`AutoModelForSeq2SeqLM` for encoder-decoder models.", FutureWarning, ) return super().from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs)