Instructions to use BJEon121/trained-sd3_backpack with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BJEon121/trained-sd3_backpack 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("BJEon121/trained-sd3_backpack") prompt = "a photo of sks backpack" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-500/optimizer.bin from BJEon121/trained-sd3_backpack: direct link, hf CLI and curl.
- Browser
- Download file 19.1 MB
-
https://huggingface.co/BJEon121/trained-sd3_backpack/resolve/main/checkpoint-500/optimizer.bin
- Command line
-
hf download hf://BJEon121/trained-sd3_backpack/checkpoint-500/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/BJEon121/trained-sd3_backpack/resolve/main/checkpoint-500/optimizer.bin
19.1 MB
- Xet hash:
- e663be40f87508f80e13aca391dfb90cd1a6d2953c1d3495c056b572bd445921
- Size of remote file:
- 19.1 MB
- SHA256:
- 26ee6988075406a0197b758659c5a4b70e6feedec30e3cd38132fac8f92ebe6f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.