Text-to-Image
Diffusers
Safetensors
English
StableDiffusionPipeline
sar
synthetic-aperture-radar
remote-sensing
stable-diffusion
image-generation
synthetic-data
ship-detection
earth-observation
sentinel-1
Instructions to use sylviaHoch/SAR-StableDiffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use sylviaHoch/SAR-StableDiffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("sylviaHoch/SAR-StableDiffusion", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- a8c0d733c5638b370909ab284c2434d021958652a939e6d9b3848bc13ab34fef
- Size of remote file:
- 335 MB
- SHA256:
- 4fbf15248903bbbff01bf584eabe2ebbf1297c3529fb5aa1042195548efd9b58
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