Text-to-Image
Diffusers
PyTorch
StableDiffusionPipeline
stable-diffusion
diffusion-models-class
dreambooth-hackathon
wildcard
Instructions to use baruga/ancient-maps with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use baruga/ancient-maps with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("baruga/ancient-maps", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of ancma map of beautiful flower garden." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Description
This is a Stable Diffusion model fine-tuned on a 100 ancient/old maps for the DreamBooth Hackathon 🔥 wildcard theme. To participate or learn more, visit this page.
To generate ancient/old maps, use a photo of ancma map of [your choice]. Modifiers and negative prompts may improve results. The model is not limited to classic geography, you can try gardens, cave systems, cities, planets, zodiac charts, etc.
Examples
a photo of ancma map of fiery volcano island.
a photo of ancma map of peaceful Swiss town near a lake.
a photo of ancma map of giant ant colony.
a photo of ancma map of beautiful flower garden.

Usage
from diffusers import StableDiffusionPipeline
pipeline = StableDiffusionPipeline.from_pretrained('baruga/ancient-maps')
image = pipeline().images[0]
image
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