Instructions to use richiewg3/Pig-e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use richiewg3/Pig-e with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("AdamLucek/sdxl-base-1.0-jarekl-lora", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("richiewg3/Pig-e") prompt = "hi" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("AdamLucek/sdxl-base-1.0-jarekl-lora", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("richiewg3/Pig-e")
prompt = "hi"
image = pipe(prompt).images[0]PMA

- Prompt
- hi
Model description
for me only
Trigger words
You should use pma to trigger the image generation.
Download model
Download them in the Files & versions tab.
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Model tree for richiewg3/Pig-e
Base model
stabilityai/stable-diffusion-xl-base-1.0