| - sections: | |
| - local: index | |
| title: 🤗 Accelerate | |
| - local: basic_tutorials/install | |
| title: Installation | |
| - local: quicktour | |
| title: Quicktour | |
| title: Getting started | |
| - sections: | |
| - local: basic_tutorials/overview | |
| title: Overview | |
| - local: basic_tutorials/migration | |
| title: Migrating to 🤗 Accelerate | |
| - local: basic_tutorials/launch | |
| title: Launching distributed code | |
| - local: basic_tutorials/notebook | |
| title: Launching distributed training from Jupyter Notebooks | |
| - local: basic_tutorials/troubleshooting | |
| title: Troubleshooting guide | |
| title: Tutorials | |
| - sections: | |
| - local: usage_guides/explore | |
| title: Start Here! | |
| - local: usage_guides/training_zoo | |
| title: Example Zoo | |
| - local: usage_guides/big_modeling | |
| title: How to perform inference on large models with small resources | |
| - local: usage_guides/model_size_estimator | |
| title: Knowing how big of a model you can fit into memory | |
| - local: usage_guides/quantization | |
| title: How to quantize model | |
| - local: usage_guides/distributed_inference | |
| title: How to perform distributed inference with normal resources | |
| - local: usage_guides/gradient_accumulation | |
| title: Performing gradient accumulation | |
| - local: usage_guides/local_sgd | |
| title: Accelerating training with local SGD | |
| - local: usage_guides/checkpoint | |
| title: Saving and loading training states | |
| - local: usage_guides/tracking | |
| title: Using experiment trackers | |
| - local: usage_guides/mps | |
| title: How to use Apple Silicon M1 GPUs | |
| - local: usage_guides/low_precision_training | |
| title: How to train in low precision (FP8) | |
| - local: usage_guides/deepspeed | |
| title: How to use DeepSpeed | |
| - local: usage_guides/fsdp | |
| title: How to use Fully Sharded Data Parallelism | |
| - local: usage_guides/megatron_lm | |
| title: How to use Megatron-LM | |
| - local: usage_guides/sagemaker | |
| title: How to use 🤗 Accelerate with SageMaker | |
| - local: usage_guides/ipex | |
| title: How to use 🤗 Accelerate with Intel® Extension for PyTorch for cpu | |
| title: How-To Guides | |
| - sections: | |
| - local: concept_guides/internal_mechanism | |
| title: 🤗 Accelerate's internal mechanism | |
| - local: concept_guides/big_model_inference | |
| title: Loading big models into memory | |
| - local: concept_guides/performance | |
| title: Comparing performance across distributed setups | |
| - local: concept_guides/deferring_execution | |
| title: Executing and deferring jobs | |
| - local: concept_guides/gradient_synchronization | |
| title: Gradient synchronization | |
| - local: concept_guides/low_precision_training | |
| title: How training in low-precision environments is possible (FP8) | |
| - local: concept_guides/training_tpu | |
| title: TPU best practices | |
| title: Concepts and fundamentals | |
| - sections: | |
| - local: package_reference/accelerator | |
| title: Main Accelerator class | |
| - local: package_reference/state | |
| title: Stateful configuration classes | |
| - local: package_reference/cli | |
| title: The Command Line | |
| - local: package_reference/torch_wrappers | |
| title: Torch wrapper classes | |
| - local: package_reference/tracking | |
| title: Experiment trackers | |
| - local: package_reference/launchers | |
| title: Distributed launchers | |
| - local: package_reference/deepspeed | |
| title: DeepSpeed utilities | |
| - local: package_reference/logging | |
| title: Logging | |
| - local: package_reference/big_modeling | |
| title: Working with large models | |
| - local: package_reference/kwargs | |
| title: Kwargs handlers | |
| - local: package_reference/utilities | |
| title: Utility functions and classes | |
| - local: package_reference/megatron_lm | |
| title: Megatron-LM Utilities | |
| - local: package_reference/fsdp | |
| title: Fully Sharded Data Parallelism Utilities | |
| title: "Reference" | |