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:
- 6adf1a9a405926dcf4c55ad3711a1c3dd9f9b9b4586b8fa0ca7319396a30c0ec
- Size of remote file:
- 9.6 MB
- SHA256:
- 54f03c01ef21698aa917988719ad33f94fe87d5bef0a4a511faea5358d2a330d
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