Instructions to use nomnomnomz/last with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nomnomnomz/last with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("nomnomnomz/last", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 5ae35db3174bda5346b1666a8d30045df3cd022a79a4ab29418a60913096cf47
- Size of remote file:
- 492 MB
- SHA256:
- 54f8d9664b67935c7dbd7f77b1c4ac8d88257a86b45468edf756962b7d10bf65
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