Skip to content

Updated lora inference instructions #6913

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
sayakpaul merged 5 commits into from
Feb 13, 2024
Merged

Updated lora inference instructions #6913

Changes from all commits
Commits
Show all changes
5 commits
Select commit Hold shift + click to select a range
65faf25
Updated lora inference instructions
AlexUmnov Feb 8, 2024
e95c300
Update examples/dreambooth/README.md
AlexUmnov Feb 9, 2024
a77a98e
Update README.md
AlexUmnov Feb 9, 2024
a534bc9
Update README.md
AlexUmnov Feb 9, 2024
cd5dbe3
Merge branch 'main' into patch-1
sayakpaul Feb 13, 2024
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
12 changes: 4 additions & 8 deletions examples/dreambooth/README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -376,18 +376,14 @@ After training, LoRA weights can be loaded very easily into the original pipelin
load the original pipeline:

```python
from diffusers import DiffusionPipeline, DPMSolverMultistepScheduler
import torch

pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.float16)
pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
pipe.to("cuda")
from diffusers import DiffusionPipeline
pipe = DiffusionPipeline.from_pretrained("base-model-name").to("cuda")
```

Next, we can load the adapter layers into the UNet with the [`load_attn_procs` function](https://huggingface.co/docs/diffusers/api/loaders#diffusers.loaders.UNet2DConditionLoadersMixin.load_attn_procs).
Next, we can load the adapter layers into the pipeline with the [`load_lora_weights` function](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters#lora).

```python
pipe.unet.load_attn_procs("patrickvonplaten/lora_dreambooth_dog_example")
pipe.load_lora_weights("path-to-the-lora-checkpoint")
```

Finally, we can run the model in inference.
Expand Down