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:
- 88210b49f752814cc74987fa64acea7c83de6ee16919bc5f9880378373e58d91
- Size of remote file:
- 122 MB
- SHA256:
- 67802458e11a740e7617a7eff2e1e52197f7e0e24eeafb1bafdb57156ef242fd
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