Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
stable-diffusion
medical-imaging
chest-xray
diffusion
Instructions to use P-RAJIV/cxr_stable_diffusion_v1_4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use P-RAJIV/cxr_stable_diffusion_v1_4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("P-RAJIV/cxr_stable_diffusion_v1_4", 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:
- 8c94cb88a73a99d79757ab4811c6a5d5d84e0a80a89849f74945f638a56250db
- Size of remote file:
- 6.88 GB
- SHA256:
- d4bd117c73587ca703944279656a5277524ff59e91f7893f36f90cc2ee019c8d
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