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
| # VAE | |
| `vae_roundtrip.py` Demonstrates the use of a VAE by roundtripping an image through the encoder and decoder. Original and reconstructed images are displayed side by side. | |
| ``` | |
| cd examples/research_projects/vae | |
| python vae_roundtrip.py \ | |
| --pretrained_model_name_or_path="stable-diffusion-v1-5/stable-diffusion-v1-5" \ | |
| --subfolder="vae" \ | |
| --input_image="/path/to/your/input.png" | |
| ``` | |