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", 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:
- 4aede540b36ba6bfa45ecdbb828f22042edc94dd5aa0d48b8714c377867adaa2
- Size of remote file:
- 5.11 MB
- SHA256:
- 0f4dfa6b0f53bc2ada3163b1fe5ecd3b580a158d6d4c64aa435dc1aba3fa905f
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