Instructions to use cremepuff/trained-sd3-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cremepuff/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("cremepuff/trained-sd3-lora") prompt = "some makeup placed on a dressing table in the style <1>" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download image_0.png from cremepuff/trained-sd3-lora: direct link, hf CLI and curl.
- Browser
- Download file 1.53 MB
-
https://huggingface.co/cremepuff/trained-sd3-lora/resolve/main/image_0.png
- Command line
-
hf download hf://cremepuff/trained-sd3-lora/image_0.png
-
curl -L -o image_0.png https://huggingface.co/cremepuff/trained-sd3-lora/resolve/main/image_0.png
1.53 MB

- Xet hash:
- d2f6fcb98ed4808b92da25fb5fd981f5bf208b532a4b90458c564b6f251c2ac0
- Size of remote file:
- 1.53 MB
- SHA256:
- 115b464928a696492ab36bec29215103725be83872c5a228fe51412dc9ba152b
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