Instructions to use iamkaikai/CLASSICAL-LORA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use iamkaikai/CLASSICAL-LORA 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("iamkaikai/CLASSICAL-LORA") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 7ac75bf602f20cb11dd33017ede72577ec4b9e01aadfbb15c13da38095063568
- Size of remote file:
- 204 MB
- SHA256:
- 98eab420903363cae4e31e749202b45184b1df9e9e8d25522ca6b4e93c8184ff
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