Instructions to use ATH-MaaS/Meissonic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ATH-MaaS/Meissonic with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ATH-MaaS/Meissonic", 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
Commit History
-
Update README.md
Verified signatureafd39d9 -
Upload architecture.png
Verified signature2b41382 -
Delete assets
Verified signaturee421455 -
Create assets/.
Verified signature32bb11e -
Delete assets
Verified signature1f29718 -
Create assets/
Verified signature906f9d3 -
Update README.md
Verified signatured4287aa
-
Update README.md
Verified signature3e5c653 -
Update README.md
Verified signaturea881ec5 -
Update README.md
Verified signature1e9c231 -
x
渊旷7bfcf76 -
initial commit
Verified signature7ed4dfb