Instructions to use agmjd/castonelight with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use agmjd/castonelight with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Mr-J-369/RealHotSpice-SD1.5-qnn2.28", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("agmjd/castonelight") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
https://civitai.com/models/588152/calstone-light-o-umamusume
- Prompt
- -
Download model
Download them in the Files & versions tab.
- Downloads last month
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Model tree for agmjd/castonelight
Base model
Mr-J-369/RealHotSpice-SD1.5-qnn2.28