Instructions to use tera0711/lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tera0711/lora 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-3.5-large", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("tera0711/lora") prompt = "<lora:guiltyficial_reality-01:0.7>, perfect body, ultra realistic, best quality, 8k uhd, masterpiece, asian beautiful woman, " 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/image (3).png
text: >-
<lora:guiltyficial_reality-01:0.7>, perfect body, ultra realistic, best
quality, 8k uhd, masterpiece, asian beautiful woman,
parameters:
negative_prompt: >-
low quality, worst quality, jpeg artifacts, unrealistic, cartoon, anime,
drawing, painting, blurry,
base_model: stabilityai/stable-diffusion-3.5-large
instance_prompt: null
license: creativeml-openrail-m
lora
.png)
- Prompt
- <lora:guiltyficial_reality-01:0.7>, perfect body, ultra realistic, best quality, 8k uhd, masterpiece, asian beautiful woman,
- Negative Prompt
- low quality, worst quality, jpeg artifacts, unrealistic, cartoon, anime, drawing, painting, blurry,
Download model
Download them in the Files & versions tab.