| - sections: |
| - local: index |
| title: 🤗 Transformers 简介 |
| - local: quicktour |
| title: 快速上手 |
| - local: installation |
| title: 安装 |
| title: 开始使用 |
| - sections: |
| - local: pipeline_tutorial |
| title: 使用pipelines进行推理 |
| - local: autoclass_tutorial |
| title: 使用AutoClass编写可移植的代码 |
| - local: preprocessing |
| title: 预处理数据 |
| - local: training |
| title: 微调预训练模型 |
| - local: run_scripts |
| title: 通过脚本训练模型 |
| - local: accelerate |
| title: 使用🤗Accelerate进行分布式训练 |
| - local: peft |
| title: 使用🤗 PEFT加载和训练adapters |
| - local: model_sharing |
| title: 分享您的模型 |
| - local: llm_tutorial |
| title: 使用LLMs进行生成 |
| title: 教程 |
| - sections: |
| - isExpanded: false |
| sections: |
| - local: tasks/asr |
| title: 自动语音识别 |
| - sections: |
| - local: fast_tokenizers |
| title: 使用 🤗 Tokenizers 中的分词器 |
| - local: multilingual |
| title: 使用多语言模型进行推理 |
| - local: create_a_model |
| title: 使用特定于模型的 API |
| - local: custom_models |
| title: 共享自定义模型 |
| - local: chat_templating |
| title: 聊天模型的模板 |
| - local: serialization |
| title: 导出为 ONNX |
| - local: gguf |
| title: 与 GGUF 格式的互操作性 |
| - local: tiktoken |
| title: 与 Tiktoken 文件的互操作性 |
| - local: community |
| title: 社区资源 |
| title: 开发者指南 |
| - sections: |
| - local: performance |
| title: 综述 |
| - sections: |
| - local: fsdp |
| title: 完全分片数据并行 |
| - local: perf_train_special |
| title: 在 Apple silicon 芯片上进行 PyTorch 训练 |
| - local: perf_infer_gpu_multi |
| title: 多GPU推理 |
| - local: perf_train_cpu |
| title: 在CPU上进行高效训练 |
| - local: perf_hardware |
| title: 用于训练的定制硬件 |
| - local: hpo_train |
| title: 使用Trainer API 进行超参数搜索 |
| title: 高效训练技术 |
| - local: big_models |
| title: 实例化大模型 |
| - local: debugging |
| title: 问题定位及解决 |
| - local: perf_torch_compile |
| title: 使用 `torch.compile()` 优化推理 |
| title: 性能和可扩展性 |
| - sections: |
| - local: contributing |
| title: 如何为 🤗 Transformers 做贡献？ |
| - local: add_new_pipeline |
| title: 如何将流水线添加到 🤗 Transformers？ |
| title: 贡献 |
| - sections: |
| - local: philosophy |
| title: Transformers的设计理念 |
| - local: task_summary |
| title: 🤗Transformers能做什么 |
| - local: tokenizer_summary |
| title: 分词器的摘要 |
| - local: attention |
| title: 注意力机制 |
| - local: bertology |
| title: 基于BERT进行的相关研究 |
| title: 概念指南 |
| - sections: |
| - sections: |
| - local: main_classes/callback |
| title: Callbacks |
| - local: main_classes/configuration |
| title: Configuration |
| - local: main_classes/data_collator |
| title: Data Collator |
| - local: main_classes/logging |
| title: Logging |
| - local: main_classes/model |
| title: 模型 |
| - local: main_classes/text_generation |
| title: 文本生成 |
| - local: main_classes/optimizer_schedules |
| title: Optimization |
| - local: main_classes/output |
| title: 模型输出 |
| - local: main_classes/pipelines |
| title: Pipelines |
| - local: main_classes/processors |
| title: Processors |
| - local: main_classes/quantization |
| title: Quantization |
| - local: main_classes/tokenizer |
| title: Tokenizer |
| - local: main_classes/trainer |
| title: Trainer |
| - local: main_classes/deepspeed |
| title: DeepSpeed集成 |
| - local: main_classes/feature_extractor |
| title: Feature Extractor |
| - local: main_classes/image_processor |
| title: Image Processor |
| title: 主要类 |
| - sections: |
| - local: internal/modeling_utils |
| title: 自定义层和工具 |
| - local: internal/pipelines_utils |
| title: pipelines工具 |
| - local: internal/tokenization_utils |
| title: Tokenizers工具 |
| - local: internal/trainer_utils |
| title: 训练器工具 |
| - local: internal/generation_utils |
| title: 生成工具 |
| - local: internal/image_processing_utils |
| title: 图像处理工具 |
| - local: internal/audio_utils |
| title: 音频处理工具 |
| - local: internal/file_utils |
| title: 通用工具 |
| - local: internal/time_series_utils |
| title: 时序数据工具 |
| - sections: |
| - local: model_doc/bert |
| title: BERT |
| title: 内部辅助工具 |
| title: 应用程序接口 (API) |
