Instructions to use alastandy/capybara2_sd3_dev_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use alastandy/capybara2_sd3_dev_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("alastandy/capybara2_sd3_dev_lora") prompt = "a drawing of a capybaracartoon" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 4f3d20d0bd3dedd7f080b064350ba017d96214ad153ed3ba2f2f2941b19a8faa
- Size of remote file:
- 19.1 MB
- SHA256:
- 55ca458d16068f04cd042100d8bf3fcea088a186984955c350276b5d9b9140ad
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.