---
license: apache-2.0
library_name: diffusers
pipeline_tag: text-to-image
widget:
- text: city neighborhood
  output:
    url: 7d3aebe3-a08d-4a31-b5ac-06408e0c835a.jpeg
- text: resort in hawaii
  output:
    url: a983aca6-9deb-41f5-8e8a-b7932cc83ff4.jpeg
- text: factory
  output:
    url: be2fb507-af99-4258-a90f-c0df2bbab3ce.jpeg
- text: university campus
  output:
    url: 12bbc23c-850a-484b-99a6-478c19417993.jpeg
---

# Model Card for Model ID

<!-- Provide a quick summary of what the model is/does. -->
This is a StableDiffusion based model that synthesizes satellite images given text prompts. The base stable diffusion model used is [stable-diffusion-2-1-base](https://huggingface.co./stabilityai/stable-diffusion-2-1-base) (v2-1_512-ema-pruned.ckpt).

  * Use it with 🧨 [diffusers](#examples)
  * Use it with [stablediffusion](https://github.com/Stability-AI/stablediffusion) repository

### Model Sources [optional]

<!-- Provide the basic links for the model. -->

- **Repository:** [stable-diffusion](https://huggingface.co./stabilityai/stable-diffusion-2-1-base)

## Examples

```python
from diffusers import StableDiffusionPipeline

pipe = StableDiffusionPipeline.from_pretrained("MVRL/GeoSynth")
pipe = pipe.to("cuda:0")

image = pipe(
    "Satellite image features a city neighborhood",
).images[0]

image.save("generated_city.jpg")
```