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_3.png from cremepuff/trained-sd3-lora: direct link, hf CLI and curl.
- Browser
- Download file 1.38 MB
-
https://huggingface.co/cremepuff/trained-sd3-lora/resolve/main/image_3.png
- Command line
-
hf download hf://cremepuff/trained-sd3-lora/image_3.png
-
curl -L -o image_3.png https://huggingface.co/cremepuff/trained-sd3-lora/resolve/main/image_3.png
1.38 MB

- Xet hash:
- 373bb8d9f126beba70a9d4e8f09eba8520c7ddeec15e102a2e121d6ed60ee345
- Size of remote file:
- 1.38 MB
- SHA256:
- ff4e34f627c5ea262035c0256180d1177868f29f69feb3c3172f242e15bf4bdf
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