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:
- b0e11b4788eed86a98e25addb54f03f9e48f10074818b4626f63c2a9ca41f43d
- Size of remote file:
- 37.9 MB
- SHA256:
- dd59aefe1ab08bd5a75528059d251551375980008bd1cf8bfb0050b076906a42
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.