Skip to content
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

add lcm to documentation #479

Merged
merged 1 commit into from
Nov 29, 2023
Merged

add lcm to documentation #479

Changes from all commits
Commits
Show all changes
1 commit
Select commit
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
22 changes: 22 additions & 0 deletions docs/source/inference.mdx
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -454,3 +454,25 @@ refiner = OVStableDiffusionXLImg2ImgPipeline.from_pretrained(model_id, export=Tr
image = base(prompt=prompt, output_type="latent").images[0]
image = refiner(prompt=prompt, image=image[None, :]).images[0]
```


## Latent Consistency Models


| Task | Auto Class |
|--------------------------------------|--------------------------------------|
| `text-to-image` | `OVLatentConsistencyModelPipeline` |


### Text-to-Image

Here is an example of how you can load a Latent Consistency Models (LCMs) from [SimianLuo/LCM_Dreamshaper_v7](https://huggingface.co/SimianLuo/LCM_Dreamshaper_v7) and run inference using OpenVINO :

```python
from optimum.intel import OVLatentConsistencyModelPipeline

model_id = "SimianLuo/LCM_Dreamshaper_v7"
pipeline = OVLatentConsistencyModelPipeline.from_pretrained(model_id, export=True)
prompt = "sailing ship in storm by Leonardo da Vinci"
images = pipeline(prompt, num_inference_steps=4, guidance_scale=8.0).images
```
Loading