Text-to-Image
Diffusers
TensorBoard
stable-diffusion
stable-diffusion-diffusers
lora
macro
bioluminescence
flora
Instructions to use imaquantinizer/sd15-bioluminescent-flora-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use imaquantinizer/sd15-bioluminescent-flora-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("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("imaquantinizer/sd15-bioluminescent-flora-lora") prompt = "biolum_flora, ultra detailed macro shot of a glowing translucent orchid with vibrant neon veins, dark background, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
๐บ Bioluminescent Flora SD 1.5 LoRA
A Stable Diffusion 1.5 LoRA trained on 120 curated macro shots of glowing, translucent flora.
- Trigger Token:
biolum_flora - Base Model:
runwayml/stable-diffusion-v1-5 - Training Hardware: NVIDIA L4 (Colab)
- Epochs: 16 (480 optimization steps at batch size 4, bf16)
- Dataset:
imaquantinizer/macro-bioluminescent-flora
Usage with Diffusers
import torch
from diffusers import StableDiffusionPipeline
pipe = StableDiffusionPipeline.from_pretrained(
'runwayml/stable-diffusion-v1-5',
torch_dtype=torch.float16
).to('cuda')
pipe.load_lora_weights('imaquantinizer/sd15-bioluminescent-flora-lora')
image = pipe('biolum_flora, glowing flower', num_inference_steps=30).images[0]
image.save('output.png')
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Model tree for imaquantinizer/sd15-bioluminescent-flora-lora
Base model
runwayml/stable-diffusion-v1-5