Instructions to use ekato/tatsuyakitani with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ekato/tatsuyakitani with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ekato/tatsuyakitani") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 5391914c98216fcf292cdf48ade499c56c7220bd99630b65d855f9fe0b43b2a1
- Size of remote file:
- 64.3 kB
- SHA256:
- 9598be15d3ac1bf767a89e4fef4359f752e2323e0f6c4c19fd5a41f5b6c91afa
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