Instructions to use papigia/mona with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use papigia/mona with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("krea/Krea-2-Turbo,krea/Krea-2-Raw", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("papigia/mona") prompt = "TOK" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 48a68af07591090952bae4fb9867db169c0ed48a1f52155372d3dd1be5c58a42
- Size of remote file:
- 195 MB
- SHA256:
- f722687dfe067e448553ff33db155751668baab4683b39b6b68e8eff72b59bfa
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.