Instructions to use lime-j/GenSIRR-vae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lime-j/GenSIRR-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("lime-j/GenSIRR-vae", 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:
- 1ee93adca09d5bbec0bb13a0418e11eae990f9ce22526445d29de0b7eda5718a
- Size of remote file:
- 335 MB
- SHA256:
- 2bf4071dbbc8c5060be9ce773c0a1ba091941dd46cf487579e2fa941871806ef
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