Instructions to use maxspire/trained-sd3-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use maxspire/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("maxspire/trained-sd3-lora", dtype=torch.bfloat16, device_map="cuda") prompt = "A photo of sks dog in a bucket" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download image_3.png from maxspire/trained-sd3-lora: direct link, hf CLI and curl.
- Browser
- Download file 1.2 MB
-
https://huggingface.co/maxspire/trained-sd3-lora/resolve/main/image_3.png
- Command line
-
hf download hf://maxspire/trained-sd3-lora/image_3.png
-
curl -L -o image_3.png https://huggingface.co/maxspire/trained-sd3-lora/resolve/main/image_3.png
1.2 MB

- Xet hash:
- 8cc9dc8fcd44592c65c4cd7399c1984cad0d7b1708916619931d2e32c08f4d63
- Size of remote file:
- 1.2 MB
- SHA256:
- a94d3b4af84269edaa134ff041aa752d2af3656c497026f9d1ba28c77066e370
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