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:
- 14aa0298618a2fc24352a8f4ea06d03ebe2c6c6ddd784fd120d8c43a90d95e6c
- Size of remote file:
- 4.27 GB
- SHA256:
- 67a115286b56c086b36e323cfef32d7e3afbe20c750c4386a238a11feb6872f7
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