Unconditional Image Generation
Diffusers
Safetensors
English
DDPMPipeline
Lung
Pneumonia
Covid-19
PyTorch
Instructions to use teohyc/Covid-XRay-Diffusion-Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use teohyc/Covid-XRay-Diffusion-Model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("teohyc/Covid-XRay-Diffusion-Model", 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
| { | |
| "_class_name": "DDPMPipeline", | |
| "_diffusers_version": "0.37.1", | |
| "scheduler": [ | |
| "diffusers", | |
| "DDPMScheduler" | |
| ], | |
| "unet": [ | |
| "diffusers", | |
| "UNet2DModel" | |
| ] | |
| } | |