Instructions to use gabehubner/vae-256px-8z with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use gabehubner/vae-256px-8z with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("gabehubner/vae-256px-8z", torch_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
Update metadata with huggingface_hub
Browse files
README.md
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type: image
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metrics:
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# VAE - UNet-Style Autoencoder for 256x256 Image Reconstruction
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type: image
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metrics:
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value: 9.444966316223145
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- type: LPIPS
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value: 0.16324043566279123
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value: 0.001018780385649029
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---
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# VAE - UNet-Style Autoencoder for 256x256 Image Reconstruction
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