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| # Installing xFormers | |
| We recommend the use of [xFormers](https://github.com/facebookresearch/xformers) for both inference and training. In our tests, the optimizations performed in the attention blocks allow for both faster speed and reduced memory consumption. | |
| Starting from version `0.0.16` of xFormers, released on January 2023, installation can be easily performed using pre-built pip wheels: | |
| ```bash | |
| pip install xformers | |
| ``` | |
| <Tip> | |
| The xFormers PIP package requires the latest version of PyTorch (1.13.1 as of xFormers 0.0.16). If you need to use a previous version of PyTorch, then we recommend you install xFormers from source using [the project instructions](https://github.com/facebookresearch/xformers#installing-xformers). | |
| </Tip> | |
| After xFormers is installed, you can use `enable_xformers_memory_efficient_attention()` for faster inference and reduced memory consumption, as discussed [here](fp16#memory-efficient-attention). | |
| <Tip warning={true}> | |
| According to [this issue](https://github.com/huggingface/diffusers/issues/2234#issuecomment-1416931212), xFormers `v0.0.16` cannot be used for training (fine-tune or Dreambooth) in some GPUs. If you observe that problem, please install a development version as indicated in that comment. | |
| </Tip> | |