Instructions to use ziiio/autoencoderkl_ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ziiio/autoencoderkl_ft with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ziiio/autoencoderkl_ft", 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:
- 8ec90c6191c459ea540fcd3cf508dceb1350fff3de32e8156f306ccd4c138710
- Size of remote file:
- 335 MB
- SHA256:
- 3f9ee9bd7d0ac516a9f368e984a8bbf23ae189681d7de2efd3a500a9641e644f
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