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---
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")
``` |