Instructions to use Savoia/trained-sd3-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Savoia/trained-sd3-lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Savoia/trained-sd3-lora") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 15ffaf38f6fc89b633a91caca9a2295777c75c0bec5eaedec2d026799fe0a34c
- Size of remote file:
- 151 MB
- SHA256:
- 5033b42d1207e6b021b60339166ab5ab76d297886839224b571b31e8c7be6f37
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