Instructions to use thejagstudio/LordSwaminaryan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use thejagstudio/LordSwaminaryan 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("thejagstudio/LordSwaminaryan") prompt = "Lord Swaminarayan as a mid-aged man in a white turban with a blue and silver necklace, wearing royal attire, biopic, Ashoka Tano inspired by Ram Chandra Shukla, three-quarter view photo, majestic androgynous prince, Jonathan Wayshak, traditional makeup, cinematic lighting, regal clothes, fanart, profile pic, Ayan Nag, edited." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- f1f01a3fb4e60f1f12cdbe995288bd4449dae1a34f220468a5d0ad1e89ea9f74
- Size of remote file:
- 455 kB
- SHA256:
- 247b1f4dedd1d7a8d19f6138ce9f9b5f3391eb345fc28c736612b28e57142517
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.