Instructions to use Alvinyz/lora-cube with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Alvinyz/lora-cube 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("Alvinyz/lora-cube") 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:
- 2c74022930a41b6da62f99ae30daebda9da240505db2e915c5f7eda7772e2c7a
- Size of remote file:
- 6.59 MB
- SHA256:
- 97e18c347f296bb38eb2961e0f107d2c6cc2c0dfb672217ab6f7d41906bf8e6e
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