import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("IsraelSalgado/cosmo-mom", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]Cosmo_mom Dreambooth model trained by IsraelSalgado with TheLastBen's fast-DreamBooth notebook
Test the concept via A1111 Colab fast-Colab-A1111
Sample pictures of this concept:
license: creativeml-openrail-m tags: - text-to-image
My tiny child on Stable Diffusion via Dreambooth
model by IsraelSalgado
This your the Stable Diffusion model fine-tuned the bip_logo concept taught to Stable Diffusion with Dreambooth.
It can be used by modifying the instance_prompt: bebe
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:
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Output:
example prompt: bebe with a big tiny cat, Raw Photo, 8k uhd
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