Instructions to use Heasterian/AsymmetricAutoencoderKLUpscaler with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Heasterian/AsymmetricAutoencoderKLUpscaler with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Heasterian/AsymmetricAutoencoderKLUpscaler", 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:
- 05df600c17eb24530e3f5fe6769fb1c2024c50a36c054fb1085486f992c9c75d
- Size of remote file:
- 128 MB
- SHA256:
- 9f982da0babcaf6c8ded7a5c86a2e6cb4401ac7b275b5e082f4cb75ea39a97e5
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