Instructions to use HuggingJaeuk/trained-sd3-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use HuggingJaeuk/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("HuggingJaeuk/trained-sd3-lora") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 7cc59fb4d24553bd838d96f143e0d7e56f08c79afbc77d4edfa57e21f82c161b
- Size of remote file:
- 2.61 MB
- SHA256:
- f5524b648d498fa5e8af7a30ab436e5e92a5c7eee24edcd3d780d2924731e471
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