Instructions to use zelaki/eq-vae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use zelaki/eq-vae with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("zelaki/eq-vae", 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
- Xet hash:
- 7bc8e55f01d40329cf99e0a53bf4b891120cb3859d14ecea2091f5f7a3fc4e58
- Size of remote file:
- 335 MB
- SHA256:
- 60a7ff080de0ac8f17b34ffc2fddc8e09b4778c09b0480df6ec13916a7a65b05
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