Instructions to use kliyer/LoRAdapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kliyer/LoRAdapter with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("kliyer/LoRAdapter") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
Update README.md
Browse files
README.md
CHANGED
|
@@ -1,3 +1,12 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
# Conditional LoRAdapter for Efficient 0-Shot Control & Altering of T2I Models
|
| 2 |
|
| 3 |
[](https://compvis.github.io/LoRAdapter/)[](https://arxiv.org/abs/2405.07913)
|
|
@@ -22,4 +31,4 @@ If you use this codebase or otherwise found our work valuable, please cite our p
|
|
| 22 |
archivePrefix={arXiv},
|
| 23 |
primaryClass={cs.CV}
|
| 24 |
}
|
| 25 |
-
```
|
|
|
|
| 1 |
+
---
|
| 2 |
+
library_name: diffusers
|
| 3 |
+
tags:
|
| 4 |
+
- stable diffusion
|
| 5 |
+
- lora
|
| 6 |
+
- loradapter
|
| 7 |
+
- adapter
|
| 8 |
+
- conditioning
|
| 9 |
+
---
|
| 10 |
# Conditional LoRAdapter for Efficient 0-Shot Control & Altering of T2I Models
|
| 11 |
|
| 12 |
[](https://compvis.github.io/LoRAdapter/)[](https://arxiv.org/abs/2405.07913)
|
|
|
|
| 31 |
archivePrefix={arXiv},
|
| 32 |
primaryClass={cs.CV}
|
| 33 |
}
|
| 34 |
+
```
|