Instructions to use MirageML/Tails with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MirageML/Tails with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("MirageML/Tails", 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:
- a412217a8a1bbabcf78de33ce089ef9ff003b5fe3df10df240fda3d40c24e4a1
- Size of remote file:
- 3.46 GB
- SHA256:
- a0f4e4f424e88f6c4cccc5b7bbb8ce851f103987d2db1fa804c37e734bc249a7
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