Instructions to use Shinhati2023/Joy_Rae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Shinhati2023/Joy_Rae 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("Shinhati2023/Joy_Rae") prompt = "A beautiful woman, very short hair, sweater vest, 8k resolution" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- template:sd-lora
widget:
- text: A beautiful woman, very short hair, sweater vest, 8k resolution
parameters:
negative_prompt: 'easy negative '
output:
url: images/1000379017.png
base_model: stabilityai/stable-diffusion-xl-base-1.0
instance_prompt: FTK
license: openrail
Joy_Rae

- Prompt
- A beautiful woman, very short hair, sweater vest, 8k resolution
- Negative Prompt
- easy negative
Trigger words
You should use FTK to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.