FastCkpt: accelerate your LLM training in one line!

Fast gradient checkpoint is designed for accelerate the training with memory-efficient attention like FlashAttention and LightSeq. FastCkpt has monkey patch for both rematerialization-aware checkpointing and FlashAttention, so you can patch both in only one line!

Paper: https://arxiv.org/pdf/2310.03294.pdf

News

• [2023/10] FastCkpt now supports LlamaModel in Huggingface!

Install

pip install fastckpt

Usage

FastCkpt now supports HF training pipeline.

Use FaskCkpt and FlashAttention

To use fasckpt with flash_attn, import and run replace_hf_ckpt_with_fast_ckpt before importing transformers

# add monkey patch for fastckpt
from fastckpt.llama_flash_attn_ckpt_monkey_patch import replace_hf_ckpt_with_fast_ckpt
replace_hf_ckpt_with_fast_ckpt()

# import transformers and other packages
import transformers
...

Use FlashAttention only

To only replace the LlamaAttention with flash_attn without chaning the checkpointing strategy, import and run replace_llama_attn_with_flash_attn

# add monkey patch for fastckpt
from fastckpt.llama_flash_attn_monkey_patch import replace_llama_attn_with_flash_attn
replace_llama_attn_with_flash_attn()

# import transformers and other packages
import transformers
...

If you find this repo useful, please cite

@article{li2023lightseq,
  title={LIGHTSEQ: SEQUENCE LEVEL PARALLELISM FOR DISTRIBUTED TRAINING OF LONG CONTEXT TRANS},
  author={Li, Dacheng and Shao, Rulin and Xie𝑠, Anze and Xing𝑐𝑚, Eric P and Gonzalez𝑏, Joseph E and Stoica𝑏, Ion and Ma𝑢, Xuezhe and Zhang𝑠, Hao},
  journal={arXiv preprint arXiv:2310.03294},
  year={2023}
}