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:
- 144cb273303163908f652d8cf8e1a46a820a3a0a191eb04fe3a4ecd03f08d12d
- Size of remote file:
- 3.4 MB
- SHA256:
- bcbbef749f8a6c12d6df59308f53a6d9ea9c78809022d1e7825f31db0a8fd0a0
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