Instructions to use gdvstd/trained-sd3-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use gdvstd/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("gdvstd/trained-sd3-lora") prompt = "a storyboard image in sks style" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 816d1ac331e695e35fa61056c2bcb4f00e17b7289badfa4529e3a45480afe58c
- Size of remote file:
- 1 kB
- SHA256:
- b123620fe8afa9519a3e029f1a335b7ee360a41a441ab984dc27080c953e2d2e
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