Instructions to use BooMarshmello/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BooMarshmello/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("stable-diffusion-v1-5/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("BooMarshmello/output") prompt = "a photo of bluey-pi" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- a6ed69c6a0deac654c4ff9ffac07902d71cafbebda091c5a2b3dc27c8d98dbfd
- Size of remote file:
- 3.4 MB
- SHA256:
- 5ab1f4553a2667c2966efa9b21a7a5099b9c086fe780bc2325f22b82ab874dec
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