Text-to-Image
Diffusers
stable-diffusion
lora
template:sd-lora
city
digital art
architecture
scenery
style
vibrant
landscape
clean
Instructions to use e-n-v-y/envy-digital-painting-xl-01 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use e-n-v-y/envy-digital-painting-xl-01 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-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("e-n-v-y/envy-digital-painting-xl-01") prompt = "digital painting, infinite scifi subterranean city outside of the multiverse" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 8f2f6786347c5a1b71256a7c383a9433c35b9f7b9e4d35b874c7e82da9cab813
- Size of remote file:
- 46.7 MB
- SHA256:
- 8493bbc5c9bc4dcab45c1125d7d779f056810b4fe8422e001b5db01ccaf30059
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.