Instructions to use mespinosami/controlearth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mespinosami/controlearth with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("mespinosami/controlearth", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
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# Model description
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<!-- Provide a longer summary of what this model is/does. -->
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ControlNet model conditioned on OpenStreetMaps (OSM) to generate the corresponding satellite images.
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# Model description
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ControlNet model conditioned on OpenStreetMaps (OSM) to generate the corresponding satellite images.
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Trained on the region of the Central Belt.
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