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 Settings
- Draw Things
- DiffusionBee
| license: creativeml-openrail-m | |
| tags: | |
| - pytorch | |
| - diffusers | |
| - stable-diffusion | |
| - text-to-image | |
| - diffusion-models-class | |
| - dreambooth-hackathon | |
| - wildcard | |
| widget: | |
| - text: a photo of ancma map of beautiful flower garden. | |
| ## 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](https://huggingface.co/dreambooth-hackathon). | |
| 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 | |
| ```python | |
| from diffusers import StableDiffusionPipeline | |
| pipeline = StableDiffusionPipeline.from_pretrained('baruga/ancient-maps') | |
| image = pipeline().images[0] | |
| image | |
| ``` | |