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sections: local: index title: π€ Transformers local: quicktour title: Quick tour local: installation title: Installation title: Get started sections: local: pipeline_tutorial title: Run inference with pipelines local: autoclass_tutorial title: Write portable code with AutoClass local: preprocessing title: Preprocess data local: training title: Fine-tune a pretrained model local: run_scripts title: Train with a script local: accelerate title: Set up distributed training with π€ Accelerate local: peft title: Load and train adapters with π€ PEFT local: model_sharing title: Share your model local: agents title: Agents local: llm_tutorial title: Generation with LLMs local: conversations title: Chatting with Transformers title: Tutorials sections: isExpanded: false sections: local: tasks/sequence_classification title: Text classification local: tasks/token_classification title: Token classification local: tasks/question_answering title: Question answering local: tasks/language_modeling title: Causal language modeling local: tasks/masked_language_modeling title: Masked language modeling local: tasks/translation title: Translation local: tasks/summarization title: Summarization local: tasks/multiple_choice title: Multiple choice title: Natural Language Processing isExpanded: false sections: local: tasks/audio_classification title: Audio classification local: tasks/asr title: Automatic speech recognition title: Audio isExpanded: false sections: local: tasks/image_classification title: Image classification local: tasks/semantic_segmentation title: Image segmentation local: tasks/video_classification title: Video classification local: tasks/object_detection title: Object detection local: tasks/zero_shot_object_detection title: Zero-shot object detection local: tasks/zero_shot_image_classification title: Zero-shot image classification local: tasks/monocular_depth_estimation title: Depth estimation local: tasks/image_to_image title: Image-to-Image local: tasks/image_feature_extraction title: Image Feature Extraction local: tasks/mask_generation title: Mask Generation local: tasks/knowledge_distillation_for_image_classification title: Knowledge Distillation for Computer Vision title: Computer Vision isExpanded: false sections: local: tasks/image_captioning title: Image captioning local: tasks/document_question_answering title: Document Question Answering local: tasks/visual_question_answering title: Visual Question Answering local: tasks/text-to-speech title: Text to speech title: Multimodal isExpanded: false sections: local: generation_strategies title: Customize the generation strategy title: Generation isExpanded: false sections: local: tasks/idefics title: Image tasks with IDEFICS local: tasks/prompting title: LLM prompting guide title: Prompting title: Task Guides sections: local: fast_tokenizers title: Use fast tokenizers from π€ Tokenizers local: multilingual title: Run inference with multilingual models local: create_a_model title: Use model-specific APIs local: custom_models title: Share a custom model local: chat_templating title: Templates for chat models local: trainer title: Trainer local: sagemaker title: Run training on Amazon SageMaker local: serialization title: Export to ONNX local: tflite title: Export to TFLite local: torchscript title: Export to TorchScript local: benchmarks title: Benchmarks local: notebooks title: Notebooks with examples local: community title: Community resources local: troubleshooting title: Troubleshoot local: gguf title: Interoperability with GGUF files title: Developer guides sections: local: quantization/overview title: Getting started local: quantization/bitsandbytes title: bitsandbytes local: quantization/gptq title: GPTQ local: quantization/awq title: AWQ local: quantization/aqlm title: AQLM local: quantization/quanto title: Quanto local: quantization/eetq title: EETQ local: quantization/hqq title: HQQ local: quantization/optimum title: Optimum local: quantization/contribute title: Contribute new quantization method title: Quantization Methods sections: local: performance title: Overview local: llm_optims title: LLM inference optimization sections: local: perf_train_gpu_one title: Methods and tools for efficient training on a single GPU local: perf_train_gpu_many title: Multiple GPUs and parallelism local: fsdp title: Fully Sharded Data Parallel local: deepspeed title: DeepSpeed local: perf_train_cpu title: Efficient training on CPU local: perf_train_cpu_many title: Distributed CPU training local: perf_train_tpu_tf title: Training on TPU with TensorFlow local: perf_train_special title: PyTorch training on Apple silicon local: perf_hardware title: Custom hardware for training local: hpo_train title: Hyperparameter Search using Trainer API title: Efficient training techniques sections: local: perf_infer_cpu title: CPU inference local: perf_infer_gpu_one title: GPU inference title: Optimizing inference local: big_models title: Instantiate a big model local: debugging title: Debugging local: tf_xla title: XLA Integration for TensorFlow Models local: perf_torch_compile title: Optimize inference using torch.compile() title: Performance and scalability sections: local: contributing title: How to contribute to π€ Transformers? local: add_new_model title: How to add a model to π€ Transformers? local: add_new_pipeline title: How to add a pipeline to π€ Transformers? local: testing title: Testing local: pr_checks title: Checks on a Pull Request title: Contribute sections: local: philosophy title: Philosophy local: glossary title: Glossary local: task_summary title: What π€ Transformers can do local: tasks_explained title: How π€ Transformers solve tasks local: model_summary title: The Transformer model family local: tokenizer_summary title: Summary of the tokenizers local: attention title: Attention mechanisms local: pad_truncation title: Padding and truncation local: bertology title: BERTology local: perplexity title: Perplexity of fixed-length models local: pipeline_webserver title: Pipelines for webserver inference local: model_memory_anatomy title: Model training anatomy local: llm_tutorial_optimization title: Getting the most out of LLMs title: Conceptual guides sections: sections: local: main_classes/agent title: Agents and Tools local: model_doc/auto title: Auto Classes local: main_classes/backbones title: Backbones local: main_classes/callback title: Callbacks local: main_classes/configuration title: Configuration local: main_classes/data_collator title: Data Collator local: main_classes/keras_callbacks title: Keras callbacks local: main_classes/logging title: Logging local: main_classes/model title: Models local: main_classes/text_generation title: Text Generation local: main_classes/onnx title: ONNX local: main_classes/optimizer_schedules title: Optimization local: main_classes/output title: Model outputs 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 local: main_classes/feature_extractor title: Feature Extractor local: main_classes/image_processor title: Image Processor title: Main Classes |