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:
- 77c194db5487911e60e741d841bde3fb770fe2c9ddd00064dca8df8529553563
- Size of remote file:
- 2.61 MB
- SHA256:
- 2312a7818a4f69f045188f8ef9310690f42d0082445b06720a83aea1c7c9e66a
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