Instructions to use ishikawa/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ishikawa/model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ishikawa/model") prompt = "a painting of sks terada" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 33bd96353b0a2ca04e94e93cfdbeec90bcd678b46810d7337ea9cd5dd47ad3fa
- Size of remote file:
- 6.59 MB
- SHA256:
- 6b7e09a3d2166856d7eedf03c94c1886f233582bfc80e5ebb9c0d3679b7fe3ef
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