Instructions to use MomlessTomato/eli-ayase with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MomlessTomato/eli-ayase 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-3.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("MomlessTomato/eli-ayase") prompt = "masterpiece, high quality, defined pupil, looking at viewer, rounded pupil, defined iris, (soft iris:1.2)," image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- f335db91fd012cd97d5b022a6939dfed4610c44647929795998ba252d2a38853
- Size of remote file:
- 1.62 GB
- SHA256:
- 8b80d21e3e303022a4b829e3a95edb3584e905c93cbb3018afeecabfb144b2a1
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