Instructions to use maxspire/scarpo-2-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use maxspire/scarpo-2-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("maxspire/scarpo-2-lora", dtype=torch.bfloat16, device_map="cuda") prompt = "An illustration of scarpo dressed as a barbarian" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 237af67de95254daeff2e9b77c24d4507e3df0c25e4ed212ae701fe3a63adf9b
- Size of remote file:
- 9.6 MB
- SHA256:
- b72183faf1e0b9e210744257f1a5935c920961ed93a442c7313f152be5a33501
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