Instructions to use johnowhitaker/lora_pn03_036sim with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use johnowhitaker/lora_pn03_036sim with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("playgroundai/playground-v2-1024px-aesthetic", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("johnowhitaker/lora_pn03_036sim") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
LoRA text2image fine-tuning - johnowhitaker/lora_pn03_036sim
These are LoRA adaption weights for playgroundai/playground-v2-1024px-aesthetic. The weights were fine-tuned on a custom dataset.

Usage:
import torch
from diffusers import DiffusionPipeline
device = "cuda:7"
pipe = DiffusionPipeline.from_pretrained(
'playgroundai/playground-v2-1024px-aesthetic',
torch_dtype=torch.float16,
add_watermarker=False,
variant="fp16"
)
pipe.to(device)
pipe.load_lora_weights('johnowhitaker/lora_pn03_036sim')
pipe("An owl wearing a tophat and tie, studio lighting, black background").images[0]
LoRA for the text encoder was enabled: False.
Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
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Model tree for johnowhitaker/lora_pn03_036sim
Base model
playgroundai/playground-v2-1024px-aesthetic