本项目为 HuggingFace transformers 库的中文文档，仅仅针对英文文档进行了翻译工作，版权归HuggingFace 团队所有。
文档的github地址：
1. 开始使用
2. 教程
3. 任务指南
3.1 自然语言处理
3.2 语音处理
3.3 机器视觉
3.4 多模态
3.5 生成
3.6 提示
4. 开发者指南：
5. 性能和可拓展性：
5.2 高效训练技巧
5.3 优化推理
5.4 其他内容
href="https://github.com/liuzard/transformers_zh_docs/blob/master/docs_zh/perf_torch_compile.md">使用torch.compile](https://github.com/liuzard/transformers_zh_docs/blob/master/docs_zh/.md)优化推理
6. 给transformers贡献
7. 概念指南 - 哲学 - 术语表 - Transformers能做什么 - Transformers如何解决任务 - Transformer模型系列 - 分词器概述 - 注意力机制 - 填充和截断 - BERTology - 固定长度模型的困惑度 - 用于Web服务器推论的流水线 - 模型训练解剖学
7 API
7.1 主要的类 - Agents and Tools - Auto Classes - Callbacks - Configuration - Data Collator - Keras callbacks - Logging - Models - Text Generation - ONNX - Optimization - Model outputs - Pipelines - Processors - Quantization - Tokenizer - Trainer - DeepSpeed Integration - Feature Extractor - Image Processor
7.2 模型
7.2.1 文本模型 - ALBERT - BART - BARThez - BARTpho - BERT - BertGeneration - BertJapanese - Bertweet - BigBird - BigBirdPegasus - BioGpt - Blenderbot - Blenderbot Small - BLOOM - BORT - ByT5 - CamemBERT - CANINE - CodeGen - CodeLlama - ConvBERT - CPM - CPMANT - CTRL - DeBERTa - DeBERTa-v2 - DialoGPT - DistilBERT - DPR - ELECTRA - Encoder Decoder Models - ERNIE - ErnieM - ESM - Falcon - FLAN-T5 - FLAN-UL2 - FlauBERT - FNet - FSMT - Funnel Transformer - GPT - GPT Neo - GPT NeoX - GPT NeoX Japanese - GPT-J - GPT2 - GPTBigCode - GPTSAN Japanese - GPTSw3 - HerBERT - I-BERT - Jukebox - LED - LLaMA - Llama2 - Longformer - LongT5 - LUKE - M2M100 - MarianMT - MarkupLM - MBart and MBart-50 - MEGA - MegatronBERT - MegatronGPT2 - mLUKE - MobileBERT - MPNet - MPT - MRA - MT5 - MVP - NEZHA - NLLB - NLLB-MoE - Nyströmformer - Open-Llama - OPT - Pegasus - PEGASUS-X - Persimmon - PhoBERT - PLBart - ProphetNet - QDQBert - RAG - REALM - Reformer - RemBERT - RetriBERT - RoBERTa - RoBERTa-PreLayerNorm - RoCBert - RoFormer - RWKV - Splinter - SqueezeBERT - SwitchTransformers - T5 - T5v1.1 - TAPEX - Transformer XL - UL2 - UMT5 - X-MOD - XGLM - XLM - XLM-ProphetNet - XLM-RoBERTa - XLM-RoBERTa-XL - XLM-V - XLNet - YOSO
7.2.2 视觉模型 - BEiT - BiT - Conditional DETR - ConvNeXT - ConvNeXTV2 - CvT - Deformable DETR - DeiT - DETA - DETR - DiNAT - DINO V2 - DiT - DPT - EfficientFormer - EfficientNet - FocalNet - GLPN - ImageGPT - LeViT - Mask2Former - MaskFormer - MobileNetV1 - MobileNetV2 - MobileViT - MobileViTV2 - NAT - PoolFormer - Pyramid Vision Transformer - RegNet - ResNet - SegFormer - SwiftFormer - Swin Transformer - Swin Transformer V2 - Swin2SR - Table Transformer - TimeSformer - UperNet - VAN - VideoMAE - Vision Transformer - ViT Hybrid - ViTDet - ViTMAE - ViTMatte - ViTMSN - ViViT - YOLOS
7.2.3 语音模型 - Audio Spectrogram Transformer - Bark - CLAP - EnCodec - Hubert - MCTCT - MMS - MusicGen - Pop2Piano - SEW - SEW-D - Speech2Text - Speech2Text2 - SpeechT5 - UniSpeech - UniSpeech-SAT - VITS - Wav2Vec2 - Wav2Vec2-Conformer - Wav2Vec2Phoneme - WavLM - Whisper - XLS-R - XLSR-Wav2Vec2
7.2.4 多模态模型 - ALIGN - AltCLIP - BLIP - BLIP-2 - BridgeTower - BROS - Chinese-CLIP - CLIP - CLIPSeg - Data2Vec - DePlot - Donut - FLAVA - GIT - GroupViT - IDEFICS - InstructBLIP - LayoutLM - LayoutLMV2 - LayoutLMV3 - LayoutXLM - LiLT - LXMERT - MatCha - MGP-STR - OneFormer - OWL-ViT - Perceiver - Pix2Struct - Segment Anything - Speech Encoder Decoder Models - TAPAS - TrOCR - TVLT - ViLT - Vision Encoder Decoder Models - Vision Text Dual Encoder - VisualBERT - X-CLIP
7.2.5 强化学习模型 - Decision Transformer - Trajectory Transformer
7.2.6 时序模型 - Autoformer - Informer - Time Series Transformer
7.2.6 图模型 - Graphormer
7.3 内部工具 - Custom Layers and Utilities - Utilities for pipelines - Utilities for Tokenizers - Utilities for Trainer - Utilities for Generation - Utilities for Image Processors - Utilities for Audio processing - General Utilities - Utilities for Time Series
