Instructions to use cagliostrolab/animagine-xl-3.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cagliostrolab/animagine-xl-3.1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("cagliostrolab/animagine-xl-3.1", dtype=torch.bfloat16, device_map="cuda") prompt = "1girl, green hair, sweater, looking at viewer, upper body, beanie, outdoors, night, turtleneck, masterpiece, best quality, very aesthetic, absurdes" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 0d59b6fff8b920f2737edb0f3f4c8af3cf7ee8c6e0055bf935e072512f3e5404
- Size of remote file:
- 5.14 GB
- SHA256:
- c1e43f5fa892e1c54c99fc7caebf9c3426910ea5a730861ff89dead23b9f260e
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