Instructions to use kid502/diffusion_portrait with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kid502/diffusion_portrait with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kid502/diffusion_portrait", 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
- Xet hash:
- e8b58354be23437d1a9d435b4ef32b41784d3d81406f871d0b62ea206471a350
- Size of remote file:
- 74.2 MB
- SHA256:
- 032210b81ff1a7ae011db22539cc801ea8b2a30aaa2cfd9af13adbaa7a5e2e5f
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