# Booster Checkpoint

Author: [Hongxin Liu](https://github.com/ver217)

**Prerequisite:**
- [Booster API](./booster_api.md)

## Introduction

We've introduced the [Booster API](./booster_api.md) in the previous tutorial. In this tutorial, we will introduce how to save and load checkpoints using booster.

## Model Checkpoint

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Model must be boosted by `colossalai.booster.Booster` before saving. `checkpoint` is the path to saved checkpoint. It can be a file, if `shard=False`. Otherwise, it should be a directory. If `shard=True`, the checkpoint will be saved in a sharded way. This is useful when the checkpoint is too large to be saved in a single file. Our sharded checkpoint format is compatible with [huggingface/transformers](https://github.com/huggingface/transformers).

{{ autodoc:colossalai.booster.Booster.load_model }}

Model must be boosted by `colossalai.booster.Booster` before loading. It will detect the checkpoint format automatically, and load in corresponding way.

## Optimizer Checkpoint

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Optimizer must be boosted by `colossalai.booster.Booster` before saving.

{{ autodoc:colossalai.booster.Booster.load_optimizer }}

Optimizer must be boosted by `colossalai.booster.Booster` before loading.

## LR Scheduler Checkpoint

{{ autodoc:colossalai.booster.Booster.save_lr_scheduler }}

LR scheduler must be boosted by `colossalai.booster.Booster` before saving. `checkpoint` is the local path to checkpoint file.

{{ autodoc:colossalai.booster.Booster.load_lr_scheduler }}

LR scheduler must be boosted by `colossalai.booster.Booster` before loading. `checkpoint` is the local path to checkpoint file.

## Checkpoint design

More details about checkpoint design can be found in our discussion [A Unified Checkpoint System Design](https://github.com/hpcaitech/ColossalAI/discussions/3339).

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