AI/diffusers
1
0
Fork 0
mirror of https://github.com/huggingface/diffusers.git synced 2026-01-29 07:22:12 +03:00
Code Activity

Typo fix: torwards -> towards (#2134)

Browse Source
This commit is contained in:
RahulBhalley
2023-01-27 12:50:18 +05:30
committed by GitHub
parent c750a82374
commit 43c5ac2be7
1 changed files with 1 additions and 1 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
examples/dreambooth/README.md
View File

@@ -279,7 +279,7 @@ Low-Rank Adaption of Large Language Models was first introduced by Microsoft in
In a nutshell, LoRA allows to adapt pretrained models by adding pairs of rank-decomposition matrices to existing weights and **only** training those newly added weights. This has a couple of advantages:
- Previous pretrained weights are kept frozen so that the model is not prone to [catastrophic forgetting](https://www.pnas.org/doi/10.1073/pnas.1611835114)
- Rank-decomposition matrices have significantly fewer parameters than the original model, which means that trained LoRA weights are easily portable.
- LoRA attention layers allow to control to which extent the model is adapted torwards new training images via a `scale` parameter.
- LoRA attention layers allow to control to which extent the model is adapted towards new training images via a `scale` parameter.
[cloneofsimo](https://github.com/cloneofsimo) was the first to try out LoRA training for Stable Diffusion in
the popular [lora](https://github.com/cloneofsimo/lora) GitHub repository.