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:
- 7f071167702293688f078d8b2370202f67b3eccf75525db3d1b3afd2bbb09720
- Size of remote file:
- 6.59 MB
- SHA256:
- aa3cc66141ec973485c79f19fa98432fa89e461b21abcda8fb3d93dc1f6b8948
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