Instructions to use timduck8/sj1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use timduck8/sj1 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", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("timduck8/sj1") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/1751260672898828907_PgNTXYeu (1).jpg
text: '-'
base_model: stable-diffusion-v1-5/stable-diffusion-v1-5
instance_prompt: null
license: other
license_name: faipl-1.0-sd
license_link: LICENSE
sj1
.jpg)
- Prompt
- -
Download model
Download them in the Files & versions tab.