Instructions to use lilpotat/a3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lilpotat/a3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lilpotat/a3", 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
- Draw Things
- DiffusionBee
- Xet hash:
- 2515cc555dab87492ed264926187633df7d14bb7023a6a6ce52b0b33ba818cc1
- Size of remote file:
- 7.7 GB
- SHA256:
- 8712e20a5d65b6acaa743e8a74961eadfdf846a2c9a32160d80a80cba13ad475
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