Instructions to use MirageML/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MirageML/test 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/test", 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:
- 2963b018f6d79ce5f2939da555eefb64a30494df4b340d5359219c19e20547f1
- Size of remote file:
- 3.44 GB
- SHA256:
- 25476d104b2f0b31c8b9ae7846834518657b53e523df22a659add4b5e5f93bcb
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