Instructions to use mkshing/lora-sdxl-3drendering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mkshing/lora-sdxl-3drendering with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("mkshing/lora-sdxl-3drendering") prompt = "a dog in 3d rendering style" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
metadata
tags:
- stable-diffusion-xl
- stable-diffusion-xl-diffusers
- text-to-image
- diffusers
- lora
- template:sd-lora
widget:
- text: a dog in 3d rendering style
output:
url: '"image_0.png"'
- text: a dog in 3d rendering style
output:
url: '"image_1.png"'
- text: a dog in 3d rendering style
output:
url: '"image_2.png"'
- text: a dog in 3d rendering style
output:
url: '"image_3.png"'
base_model: stable-diffusion-xl-base-1.0 instance_prompt: a woman of in 3d rendering style license: openrail++
SDXL LoRA DreamBooth - mkshing/lora-sdxl-3drendering

- Prompt
- a dog in 3d rendering style

- Prompt
- a dog in 3d rendering style

- Prompt
- a dog in 3d rendering style

- Prompt
- a dog in 3d rendering style
Model description
These are mkshing/lora-sdxl-3drendering LoRA adaption weights for /fsx/proj-jp-stable-diffusion/models/stable-diffusion/stable-diffusion-xl-base-1.0. The weights were trained using DreamBooth. LoRA for the text encoder was enabled: False. Special VAE used for training: None.
Trigger words
You should use a woman of in 3d rendering style to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.