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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 50cea7e06a59a141004bf4eb6a50f99bd9cec4ea9cc80a30a0fd6de61a7169f8
- Size of remote file:
- 2.58 MB
- SHA256:
- 92ffb7eff28a02c251682364d5cff8c0601e1caa10b663466299bb3715f4a62a
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