# 🤗 Transformers State-of-the-art Machine Learning for [PyTorch](https://pytorch.org/), [TensorFlow](https://www.tensorflow.org/), and [JAX](https://jax.readthedocs.io/en/latest/). 🤗 Transformers provides APIs and tools to easily download and train state-of-the-art pretrained models. Using pretrained models can reduce your compute costs, carbon footprint, and save you the time and resources required to train a model from scratch. These models support common tasks in different modalities, such as: 📝 **Natural Language Processing**: text classification, named entity recognition, question answering, language modeling, summarization, translation, multiple choice, and text generation.
🖼️ **Computer Vision**: image classification, object detection, and segmentation.
🗣️ **Audio**: automatic speech recognition and audio classification.
🐙 **Multimodal**: table question answering, optical character recognition, information extraction from scanned documents, video classification, and visual question answering. 🤗 Transformers support framework interoperability between PyTorch, TensorFlow, and JAX. This provides the flexibility to use a different framework at each stage of a model's life; train a model in three lines of code in one framework, and load it for inference in another. Models can also be exported to a format like ONNX and TorchScript for deployment in production environments. Join the growing community on the [Hub](https://huggingface.co/models), [forum](https://discuss.huggingface.co/), or [Discord](https://discord.com/invite/JfAtkvEtRb) today! ## If you are looking for custom support from the Hugging Face team ## Contents The documentation is organized into five sections: - **GET STARTED** provides a quick tour of the library and installation instructions to get up and running. - **TUTORIALS** are a great place to start if you're a beginner. This section will help you gain the basic skills you need to start using the library. - **HOW-TO GUIDES** show you how to achieve a specific goal, like finetuning a pretrained model for language modeling or how to write and share a custom model. - **CONCEPTUAL GUIDES** offers more discussion and explanation of the underlying concepts and ideas behind models, tasks, and the design philosophy of 🤗 Transformers. - **API** describes all classes and functions: - **MAIN CLASSES** details the most important classes like configuration, model, tokenizer, and pipeline. - **MODELS** details the classes and functions related to each model implemented in the library. - **INTERNAL HELPERS** details utility classes and functions used internally. ## Supported models and frameworks The table below represents the current support in the library for each of those models, whether they have a Python tokenizer (called "slow"). A "fast" tokenizer backed by the 🤗 Tokenizers library, whether they have support in Jax (via Flax), PyTorch, and/or TensorFlow. | Model | PyTorch support | TensorFlow support | Flax Support | |:------------------------------------------------------------------------:|:---------------:|:------------------:|:------------:| | [ALBERT](model_doc/albert) | ✅ | ✅ | ✅ | | [ALIGN](model_doc/align) | ✅ | ❌ | ❌ | | [AltCLIP](model_doc/altclip) | ✅ | ❌ | ❌ | | [Audio Spectrogram Transformer](model_doc/audio-spectrogram-transformer) | ✅ | ❌ | ❌ | | [Autoformer](model_doc/autoformer) | ✅ | ❌ | ❌ | | [Bark](model_doc/bark) | ✅ | ❌ | ❌ | | [BART](model_doc/bart) | ✅ | ✅ | ✅ | | [BARThez](model_doc/barthez) | ✅ | ✅ | ✅ | | [BARTpho](model_doc/bartpho) | ✅ | ✅ | ✅ | | [BEiT](model_doc/beit) | ✅ | ❌ | ✅ | | [BERT](model_doc/bert) | ✅ | ✅ | ✅ | | [Bert Generation](model_doc/bert-generation) | ✅ | ❌ | ❌ | | [BertJapanese](model_doc/bert-japanese) | ✅ | ✅ | ✅ | | [BERTweet](model_doc/bertweet) | ✅ | ✅ | ✅ | | [BigBird](model_doc/big_bird) | ✅ | ❌ | ✅ | | [BigBird-Pegasus](model_doc/bigbird_pegasus) | ✅ | ❌ | ❌ | | [BioGpt](model_doc/biogpt) | ✅ | ❌ | ❌ | | [BiT](model_doc/bit) | ✅ | ❌ | ❌ | | [Blenderbot](model_doc/blenderbot) | ✅ | ✅ | ✅ | | [BlenderbotSmall](model_doc/blenderbot-small) | ✅ | ✅ | ✅ | | [BLIP](model_doc/blip) | ✅ | ✅ | ❌ | | [BLIP-2](model_doc/blip-2) | ✅ | ❌ | ❌ | | [BLOOM](model_doc/bloom) | ✅ | ❌ | ✅ | | [BORT](model_doc/bort) | ✅ | ✅ | ✅ | | [BridgeTower](model_doc/bridgetower) | ✅ | ❌ | ❌ | | [BROS](model_doc/bros) | ✅ | ❌ | ❌ | | [ByT5](model_doc/byt5) | ✅ | ✅ | ✅ | | [CamemBERT](model_doc/camembert) | ✅ | ✅ | ❌ | | [CANINE](model_doc/canine) | ✅ | ❌ | ❌ | | [Chinese-CLIP](model_doc/chinese_clip) | ✅ | ❌ | ❌ | | [CLAP](model_doc/clap) | ✅ | ❌ | ❌ | | [CLIP](model_doc/clip) | ✅ | ✅ | ✅ | | [CLIPSeg](model_doc/clipseg) | ✅ | ❌ | ❌ | | [CLVP](model_doc/clvp) | ✅ | ❌ | ❌ | | [CodeGen](model_doc/codegen) | ✅ | ❌ | ❌ | | [CodeLlama](model_doc/code_llama) | ✅ | ❌ | ✅ | | [Cohere](model_doc/cohere) | ✅ | ❌ | ❌ | | [Conditional DETR](model_doc/conditional_detr) | ✅ | ❌ | ❌ | | [ConvBERT](model_doc/convbert) | ✅ | ✅ | ❌ | | [ConvNeXT](model_doc/convnext) | ✅ | ✅ | ❌ | | [ConvNeXTV2](model_doc/convnextv2) | ✅ | ✅ | ❌ | | [CPM](model_doc/cpm) | ✅ | ✅ | ✅ | | [CPM-Ant](model_doc/cpmant) | ✅ | ❌ | ❌ | | [CTRL](model_doc/ctrl) | ✅ | ✅ | ❌ | | [CvT](model_doc/cvt) | ✅ | ✅ | ❌ | | [Data2VecAudio](model_doc/data2vec) | ✅ | ❌ | ❌ | | [Data2VecText](model_doc/data2vec) | ✅ | ❌ | ❌ | | [Data2VecVision](model_doc/data2vec) | ✅ | ✅ | ❌ | | [DBRX](model_doc/dbrx) | ✅ | ❌ | ❌ | | [DeBERTa](model_doc/deberta) | ✅ | ✅ | ❌ | | [DeBERTa-v2](model_doc/deberta-v2) | ✅ | ✅ | ❌ | | [Decision Transformer](model_doc/decision_transformer) | ✅ | ❌ | ❌ | | [Deformable DETR](model_doc/deformable_detr) | ✅ | ❌ | ❌ | | [DeiT](model_doc/deit) | ✅ | ✅ | ❌ | | [DePlot](model_doc/deplot) | ✅ | ❌ | ❌ | | [Depth Anything](model_doc/depth_anything) | ✅ | ❌ | ❌ | | [DETA](model_doc/deta) | ✅ | ❌ | ❌ | | [DETR](model_doc/detr) | ✅ | ❌ | ❌ | | [DialoGPT](model_doc/dialogpt) | ✅ | ✅ | ✅ | | [DiNAT](model_doc/dinat) | ✅ | ❌ | ❌ | | [DINOv2](model_doc/dinov2) | ✅ | ❌ | ❌ | | [DistilBERT](model_doc/distilbert) | ✅ | ✅ | ✅ | | [DiT](model_doc/dit) | ✅ | ❌ | ✅ | | [DonutSwin](model_doc/donut) | ✅ | ❌ | ❌ | | [DPR](model_doc/dpr) | ✅ | ✅ | ❌ | | [DPT](model_doc/dpt) | ✅ | ❌ | ❌ | | [EfficientFormer](model_doc/efficientformer) | ✅ | ✅ | ❌ | | [EfficientNet](model_doc/efficientnet) | ✅ | ❌ | ❌ | | [ELECTRA](model_doc/electra) | ✅ | ✅ | ✅ | | [EnCodec](model_doc/encodec) | ✅ | ❌ | ❌ | | [Encoder decoder](model_doc/encoder-decoder) | ✅ | ✅ | ✅ | | [ERNIE](model_doc/ernie) | ✅ | ❌ | ❌ | | [ErnieM](model_doc/ernie_m) | ✅ | ❌ | ❌ | | [ESM](model_doc/esm) | ✅ | ✅ | ❌ | | [FairSeq Machine-Translation](model_doc/fsmt) | ✅ | ❌ | ❌ | | [Falcon](model_doc/falcon) | ✅ | ❌ | ❌ | | [FastSpeech2Conformer](model_doc/fastspeech2_conformer) | ✅ | ❌ | ❌ | | [FLAN-T5](model_doc/flan-t5) | ✅ | ✅ | ✅ | | [FLAN-UL2](model_doc/flan-ul2) | ✅ | ✅ | ✅ | | [FlauBERT](model_doc/flaubert) | ✅ | ✅ | ❌ | | [FLAVA](model_doc/flava) | ✅ | ❌ | ❌ | | [FNet](model_doc/fnet) | ✅ | ❌ | ❌ | | [FocalNet](model_doc/focalnet) | ✅ | ❌ | ❌ | | [Funnel Transformer](model_doc/funnel) | ✅ | ✅ | ❌ | | [Fuyu](model_doc/fuyu) | ✅ | ❌ | ❌ | | [Gemma](model_doc/gemma) | ✅ | ❌ | ✅ | | [GIT](model_doc/git) | ✅ | ❌ | ❌ | | [GLPN](model_doc/glpn) | ✅ | ❌ | ❌ | | [GPT Neo](model_doc/gpt_neo) | ✅ | ❌ | ✅ | | [GPT NeoX](model_doc/gpt_neox) | ✅ | ❌ | ❌ | | [GPT NeoX Japanese](model_doc/gpt_neox_japanese) | ✅ | ❌ | ❌ | | [GPT-J](model_doc/gptj) | ✅ | ✅ | ✅ | | [GPT-Sw3](model_doc/gpt-sw3) | ✅ | ✅ | ✅ | | [GPTBigCode](model_doc/gpt_bigcode) | ✅ | ❌ | ❌ | | [GPTSAN-japanese](model_doc/gptsan-japanese) | ✅ | ❌ | ❌ | | [Graphormer](model_doc/graphormer) | ✅ | ❌ | ❌ | | [Grounding DINO](model_doc/grounding-dino) | ✅ | ❌ | ❌ | | [GroupViT](model_doc/groupvit) | ✅ | ✅ | ❌ | | [HerBERT](model_doc/herbert) | ✅ | ✅ | ✅ | | [Hubert](model_doc/hubert) | ✅ | ✅ | ❌ | | [I-BERT](model_doc/ibert) | ✅ | ❌ | ❌ | | [IDEFICS](model_doc/idefics) | ✅ | ❌ | ❌ | | [Idefics2](model_doc/idefics2) | ✅ | ❌ | ❌ | | [ImageGPT](model_doc/imagegpt) | ✅ | ❌ | ❌ | | [Informer](model_doc/informer) | ✅ | ❌ | ❌ | | [InstructBLIP](model_doc/instructblip) | ✅ | ❌ | ❌ | | [Jamba](model_doc/jamba) | ✅ | ❌ | ❌ | | [Jukebox](model_doc/jukebox) | ✅ | ❌ | ❌ | | [KOSMOS-2](model_doc/kosmos-2) | ✅ | ❌ | ❌ | | [LayoutLM](model_doc/layoutlm) | ✅ | ✅ | ❌ | | [LayoutLMv2](model_doc/layoutlmv2) | ✅ | ❌ | ❌ | | [LayoutLMv3](model_doc/layoutlmv3) | ✅ | ✅ | ❌ | | [LayoutXLM](model_doc/layoutxlm) | ✅ | ❌ | ❌ | | [LED](model_doc/led) | ✅ | ✅ | ❌ | | [LeViT](model_doc/levit) | ✅ | ❌ | ❌ | | [LiLT](model_doc/lilt) | ✅ | ❌ | ❌ | | [LLaMA](model_doc/llama) | ✅ | ❌ | ✅ | | [Llama2](model_doc/llama2) | ✅ | ❌ | ✅ | | [Llama3](model_doc/llama3) | ✅ | ❌ | ✅ | | [LLaVa](model_doc/llava) | ✅ | ❌ | ❌ | | [LLaVA-NeXT](model_doc/llava_next) | ✅ | ❌ | ❌ | | [Longformer](model_doc/longformer) | ✅ | ✅ | ❌ | | [LongT5](model_doc/longt5) | ✅ | ❌ | ✅ | | [LUKE](model_doc/luke) | ✅ | ❌ | ❌ | | [LXMERT](model_doc/lxmert) | ✅ | ✅ | ❌ | | [M-CTC-T](model_doc/mctct) | ✅ | ❌ | ❌ | | [M2M100](model_doc/m2m_100) | ✅ | ❌ | ❌ | | [MADLAD-400](model_doc/madlad-400) | ✅ | ✅ | ✅ | | [Mamba](model_doc/mamba) | ✅ | ❌ | ❌ | | [Marian](model_doc/marian) | ✅ | ✅ | ✅ | | [MarkupLM](model_doc/markuplm) | ✅ | ❌ | ❌ | | [Mask2Former](model_doc/mask2former) | ✅ | ❌ | ❌ | | [MaskFormer](model_doc/maskformer) | ✅ | ❌ | ❌ | | [MatCha](model_doc/matcha) | ✅ | ❌ | ❌ | | [mBART](model_doc/mbart) | ✅ | ✅ | ✅ | | [mBART-50](model_doc/mbart50) | ✅ | ✅ | ✅ | | [MEGA](model_doc/mega) | ✅ | ❌ | ❌ | | [Megatron-BERT](model_doc/megatron-bert) | ✅ | ❌ | ❌ | | [Megatron-GPT2](model_doc/megatron_gpt2) | ✅ | ✅ | ✅ | | [MGP-STR](model_doc/mgp-str) | ✅ | ❌ | ❌ | | [Mistral](model_doc/mistral) | ✅ | ❌ | ✅ | | [Mixtral](model_doc/mixtral) | ✅ | ❌ | ❌ | | [mLUKE](model_doc/mluke) | ✅ | ❌ | ❌ | | [MMS](model_doc/mms) | ✅ | ✅ | ✅ | | [MobileBERT](model_doc/mobilebert) | ✅ | ✅ | ❌ | | [MobileNetV1](model_doc/mobilenet_v1) | ✅ | ❌ | ❌ | | [MobileNetV2](model_doc/mobilenet_v2) | ✅ | ❌ | ❌ | | [MobileViT](model_doc/mobilevit) | ✅ | ✅ | ❌ | | [MobileViTV2](model_doc/mobilevitv2) | ✅ | ❌ | ❌ | | [MPNet](model_doc/mpnet) | ✅ | ✅ | ❌ | | [MPT](model_doc/mpt) | ✅ | ❌ | ❌ | | [MRA](model_doc/mra) | ✅ | ❌ | ❌ | | [MT5](model_doc/mt5) | ✅ | ✅ | ✅ | | [MusicGen](model_doc/musicgen) | ✅ | ❌ | ❌ | | [MusicGen Melody](model_doc/musicgen_melody) | ✅ | ❌ | ❌ | | [MVP](model_doc/mvp) | ✅ | ❌ | ❌ | | [NAT](model_doc/nat) | ✅ | ❌ | ❌ | | [Nezha](model_doc/nezha) | ✅ | ❌ | ❌ | | [NLLB](model_doc/nllb) | ✅ | ❌ | ❌ | | [NLLB-MOE](model_doc/nllb-moe) | ✅ | ❌ | ❌ | | [Nougat](model_doc/nougat) | ✅ | ✅ | ✅ | | [Nyströmformer](model_doc/nystromformer) | ✅ | ❌ | ❌ | | [OLMo](model_doc/olmo) | ✅ | ❌ | ❌ | | [OneFormer](model_doc/oneformer) | ✅ | ❌ | ❌ | | [OpenAI GPT](model_doc/openai-gpt) | ✅ | ✅ | ❌ | | [OpenAI GPT-2](model_doc/gpt2) | ✅ | ✅ | ✅ | | [OpenLlama](model_doc/open-llama) | ✅ | ❌ | ❌ | | [OPT](model_doc/opt) | ✅ | ✅ | ✅ | | [OWL-ViT](model_doc/owlvit) | ✅ | ❌ | ❌ | | [OWLv2](model_doc/owlv2) | ✅ | ❌ | ❌ | | [PatchTSMixer](model_doc/patchtsmixer) | ✅ | ❌ | ❌ | | [PatchTST](model_doc/patchtst) | ✅ | ❌ | ❌ | | [Pegasus](model_doc/pegasus) | ✅ | ✅ | ✅ | | [PEGASUS-X](model_doc/pegasus_x) | ✅ | ❌ | ❌ | | [Perceiver](model_doc/perceiver) | ✅ | ❌ | ❌ | | [Persimmon](model_doc/persimmon) | ✅ | ❌ | ❌ | | [Phi](model_doc/phi) | ✅ | ❌ | ❌ | | [Phi3](model_doc/phi3) | ✅ | ❌ | ❌ | | [PhoBERT](model_doc/phobert) | ✅ | ✅ | ✅ | | [Pix2Struct](model_doc/pix2struct) | ✅ | ❌ | ❌ | | [PLBart](model_doc/plbart) | ✅ | ❌ | ❌ | | [PoolFormer](model_doc/poolformer) | ✅ | ❌ | ❌ | | [Pop2Piano](model_doc/pop2piano) | ✅ | ❌ | ❌ | | [ProphetNet](model_doc/prophetnet) | ✅ | ❌ | ❌ | | [PVT](model_doc/pvt) | ✅ | ❌ | ❌ | | [PVTv2](model_doc/pvt_v2) | ✅ | ❌ | ❌ | | [QDQBert](model_doc/qdqbert) | ✅ | ❌ | ❌ | | [Qwen2](model_doc/qwen2) | ✅ | ❌ | ❌ | | [Qwen2MoE](model_doc/qwen2_moe) | ✅ | ❌ | ❌ | | [RAG](model_doc/rag) | ✅ | ✅ | ❌ | | [REALM](model_doc/realm) | ✅ | ❌ | ❌ | | [RecurrentGemma](model_doc/recurrent_gemma) | ✅ | ❌ | ❌ | | [Reformer](model_doc/reformer) | ✅ | ❌ | ❌ | | [RegNet](model_doc/regnet) | ✅ | ✅ | ✅ | | [RemBERT](model_doc/rembert) | ✅ | ✅ | ❌ | | [ResNet](model_doc/resnet) | ✅ | ✅ | ✅ | | [RetriBERT](model_doc/retribert) | ✅ | ❌ | ❌ | | [RoBERTa](model_doc/roberta) | ✅ | ✅ | ✅ | | [RoBERTa-PreLayerNorm](model_doc/roberta-prelayernorm) | ✅ | ✅ | ✅ | | [RoCBert](model_doc/roc_bert) | ✅ | ❌ | ❌ | | [RoFormer](model_doc/roformer) | ✅ | ✅ | ✅ | | [RWKV](model_doc/rwkv) | ✅ | ❌ | ❌ | | [SAM](model_doc/sam) | ✅ | ✅ | ❌ | | [SeamlessM4T](model_doc/seamless_m4t) | ✅ | ❌ | ❌ | | [SeamlessM4Tv2](model_doc/seamless_m4t_v2) | ✅ | ❌ | ❌ | | [SegFormer](model_doc/segformer) | ✅ | ✅ | ❌ | | [SegGPT](model_doc/seggpt) | ✅ | ❌ | ❌ | | [SEW](model_doc/sew) | ✅ | ❌ | ❌ | | [SEW-D](model_doc/sew-d) | ✅ | ❌ | ❌ | | [SigLIP](model_doc/siglip) | ✅ | ❌ | ❌ | | [Speech Encoder decoder](model_doc/speech-encoder-decoder) | ✅ | ❌ | ✅ | | [Speech2Text](model_doc/speech_to_text) | ✅ | ✅ | ❌ | | [SpeechT5](model_doc/speecht5) | ✅ | ❌ | ❌ | | [Splinter](model_doc/splinter) | ✅ | ❌ | ❌ | | [SqueezeBERT](model_doc/squeezebert) | ✅ | ❌ | ❌ | | [StableLm](model_doc/stablelm) | ✅ | ❌ | ❌ | | [Starcoder2](model_doc/starcoder2) | ✅ | ❌ | ❌ | | [SuperPoint](model_doc/superpoint) | ✅ | ❌ | ❌ | | [SwiftFormer](model_doc/swiftformer) | ✅ | ✅ | ❌ | | [Swin Transformer](model_doc/swin) | ✅ | ✅ | ❌ | | [Swin Transformer V2](model_doc/swinv2) | ✅ | ❌ | ❌ | | [Swin2SR](model_doc/swin2sr) | ✅ | ❌ | ❌ | | [SwitchTransformers](model_doc/switch_transformers) | ✅ | ❌ | ❌ | | [T5](model_doc/t5) | ✅ | ✅ | ✅ | | [T5v1.1](model_doc/t5v1.1) | ✅ | ✅ | ✅ | | [Table Transformer](model_doc/table-transformer) | ✅ | ❌ | ❌ | | [TAPAS](model_doc/tapas) | ✅ | ✅ | ❌ | | [TAPEX](model_doc/tapex) | ✅ | ✅ | ✅ | | [Time Series Transformer](model_doc/time_series_transformer) | ✅ | ❌ | ❌ | | [TimeSformer](model_doc/timesformer) | ✅ | ❌ | ❌ | | [Trajectory Transformer](model_doc/trajectory_transformer) | ✅ | ❌ | ❌ | | [Transformer-XL](model_doc/transfo-xl) | ✅ | ✅ | ❌ | | [TrOCR](model_doc/trocr) | ✅ | ❌ | ❌ | | [TVLT](model_doc/tvlt) | ✅ | ❌ | ❌ | | [TVP](model_doc/tvp) | ✅ | ❌ | ❌ | | [UDOP](model_doc/udop) | ✅ | ❌ | ❌ | | [UL2](model_doc/ul2) | ✅ | ✅ | ✅ | | [UMT5](model_doc/umt5) | ✅ | ❌ | ❌ | | [UniSpeech](model_doc/unispeech) | ✅ | ❌ | ❌ | | [UniSpeechSat](model_doc/unispeech-sat) | ✅ | ❌ | ❌ | | [UnivNet](model_doc/univnet) | ✅ | ❌ | ❌ | | [UPerNet](model_doc/upernet) | ✅ | ❌ | ❌ | | [VAN](model_doc/van) | ✅ | ❌ | ❌ | | [VideoMAE](model_doc/videomae) | ✅ | ❌ | ❌ | | [ViLT](model_doc/vilt) | ✅ | ❌ | ❌ | | [VipLlava](model_doc/vipllava) | ✅ | ❌ | ❌ | | [Vision Encoder decoder](model_doc/vision-encoder-decoder) | ✅ | ✅ | ✅ | | [VisionTextDualEncoder](model_doc/vision-text-dual-encoder) | ✅ | ✅ | ✅ | | [VisualBERT](model_doc/visual_bert) | ✅ | ❌ | ❌ | | [ViT](model_doc/vit) | ✅ | ✅ | ✅ | | [ViT Hybrid](model_doc/vit_hybrid) | ✅ | ❌ | ❌ | | [VitDet](model_doc/vitdet) | ✅ | ❌ | ❌ | | [ViTMAE](model_doc/vit_mae) | ✅ | ✅ | ❌ | | [ViTMatte](model_doc/vitmatte) | ✅ | ❌ | ❌ | | [ViTMSN](model_doc/vit_msn) | ✅ | ❌ | ❌ | | [VITS](model_doc/vits) | ✅ | ❌ | ❌ | | [ViViT](model_doc/vivit) | ✅ | ❌ | ❌ | | [Wav2Vec2](model_doc/wav2vec2) | ✅ | ✅ | ✅ | | [Wav2Vec2-BERT](model_doc/wav2vec2-bert) | ✅ | ❌ | ❌ | | [Wav2Vec2-Conformer](model_doc/wav2vec2-conformer) | ✅ | ❌ | ❌ | | [Wav2Vec2Phoneme](model_doc/wav2vec2_phoneme) | ✅ | ✅ | ✅ | | [WavLM](model_doc/wavlm) | ✅ | ❌ | ❌ | | [Whisper](model_doc/whisper) | ✅ | ✅ | ✅ | | [X-CLIP](model_doc/xclip) | ✅ | ❌ | ❌ | | [X-MOD](model_doc/xmod) | ✅ | ❌ | ❌ | | [XGLM](model_doc/xglm) | ✅ | ✅ | ✅ | | [XLM](model_doc/xlm) | ✅ | ✅ | ❌ | | [XLM-ProphetNet](model_doc/xlm-prophetnet) | ✅ | ❌ | ❌ | | [XLM-RoBERTa](model_doc/xlm-roberta) | ✅ | ✅ | ✅ | | [XLM-RoBERTa-XL](model_doc/xlm-roberta-xl) | ✅ | ❌ | ❌ | | [XLM-V](model_doc/xlm-v) | ✅ | ✅ | ✅ | | [XLNet](model_doc/xlnet) | ✅ | ✅ | ❌ | | [XLS-R](model_doc/xls_r) | ✅ | ✅ | ✅ | | [XLSR-Wav2Vec2](model_doc/xlsr_wav2vec2) | ✅ | ✅ | ✅ | | [YOLOS](model_doc/yolos) | ✅ | ❌ | ❌ | | [YOSO](model_doc/yoso) | ✅ | ❌ | ❌ |