- 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"