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:
- e5032633b65f152df1336c9a27ab4ca994cddda619b965c6670dda85d9f5322d
- Size of remote file:
- 6.59 MB
- SHA256:
- 30e15368ac1e89f3aed71762596896b6981710a812be8076a65d80299e496b19
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