Instructions to use Kvisten/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Kvisten/output with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Kvisten/output") prompt = "photo of a nobcap can" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- cef8813099cce99cd134542d2984cbb6bb5ca1f3f80fe91586ac21dfe592f05f
- Size of remote file:
- 7.92 MB
- SHA256:
- 20119bd6800a0c0e802a6403af5eace3145740a9ebe2a2acb0eb6079bf41ea9f
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