Instructions to use ACCC1380/nyako_style with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ACCC1380/nyako_style with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("circlestone-labs/Anima", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ACCC1380/nyako_style") 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
2 days ago
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Anima base Nyako LoRA: rank16 alpha16, 150 total epochs (resumed after epoch 50), training artifacts and final resume state
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Anima base Nyako LoRA: rank16 alpha16, 50 epochs, training artifacts and final resume state
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initial commit
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