pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Chicocollage/lisilinder", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]lisilinder on Stable Diffusion via Dreambooth
model by Chicocollage
This your the Stable Diffusion model fine-tuned the lisilinder concept taught to Stable Diffusion with Dreambooth.
It can be used by modifying the instance_prompt: a photo of sks lisilinder
You can also train your own concepts and upload them to the library by using this notebook.
And you can run your new concept via diffusers: Colab Notebook for Inference, Spaces with the Public Concepts loaded
Here are the images used for training this concept:
- Downloads last month
- -
# Gated model: Login with a HF token with gated access permission hf auth login