Instructions to use lsmpp/kontextrefiner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lsmpp/kontextrefiner with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lsmpp/kontextrefiner", 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
PNDMScheduler
PNDMScheduler, or pseudo numerical methods for diffusion models, uses more advanced ODE integration techniques like the Runge-Kutta and linear multi-step method. The original implementation can be found at crowsonkb/k-diffusion.
PNDMScheduler
[[autodoc]] PNDMScheduler
SchedulerOutput
[[autodoc]] schedulers.scheduling_utils.SchedulerOutput