Skip to content
Merged
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 2 additions & 0 deletions docs/source/en/perf_train_gpu_many.md
Original file line number Diff line number Diff line change
Expand Up @@ -19,6 +19,8 @@ Multi-GPU setups are effective for accelerating training and fitting large model

This guide will discuss the various parallelism methods, combining them, and choosing an appropriate strategy for your setup. For more details about distributed training, refer to the [Accelerate](https://hf.co/docs/accelerate/index) documentation.

For a comprehensive guide on scaling large language models, check out the [Ultrascale Playbook](https://huggingface.co/spaces/nanotron/ultrascale-playbook), which provides detailed strategies and best practices for training at scale.

## Scalability strategy

Use the [Model Memory Calculator](https://huggingface.co/spaces/hf-accelerate/model-memory-usage) to calculate how much memory a model requires. Then refer to the table below to select a strategy based on your setup.
Expand Down