Unconditional Image Generation
Diffusers
PyTorch
diffusion
ddpm
conditional-generation
image-to-image
scientific-imaging
x-ray
agriculture
seed-phenotyping
Instructions to use MarwenBellili/canolaxray-conditional-DDPM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MarwenBellili/canolaxray-conditional-DDPM with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("MarwenBellili/canolaxray-conditional-DDPM", 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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