Instructions to use BeQuiet94/trained-sd3-5-no_text_a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BeQuiet94/trained-sd3-5-no_text_a 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-3.5-medium", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("BeQuiet94/trained-sd3-5-no_text_a") prompt = "A dolphine in a cycle. In the lzypod1_style" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download image_0.png from BeQuiet94/trained-sd3-5-no_text_a: direct link, hf CLI and curl.
- Browser
- Download file 1.32 MB
-
https://huggingface.co/BeQuiet94/trained-sd3-5-no_text_a/resolve/main/image_0.png
- Command line
-
hf download hf://BeQuiet94/trained-sd3-5-no_text_a/image_0.png
-
curl -L -o image_0.png https://huggingface.co/BeQuiet94/trained-sd3-5-no_text_a/resolve/main/image_0.png
1.32 MB

- Xet hash:
- 7c6d3541d9e3d4711786a48355447be5df12948971fc1f69365385aadce8048f
- Size of remote file:
- 1.32 MB
- SHA256:
- 65ca7ccc1119f5b50ebeca64a4bb6d9241f88bc06c6558e1db39a7c2ccf899ad
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.