Instructions to use EarthnDusk/Loras_2023 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use EarthnDusk/Loras_2023 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("EarthnDusk/Loras_2023") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 8cfaf6a11a8ae7cc4fd4357bc37a1daed2fcc5c74221c5b26529dedd3e213c8c
- Size of remote file:
- 37.9 MB
- SHA256:
- 2badf2fa528b56e43e03441577916c53721dc6a08672f71de082c78efa6ae9f4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.