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:
- 9b07007314fc384345c2b6e4da76e5b509689cf0b276e0b932913c64780ad633
- Size of remote file:
- 3.4 MB
- SHA256:
- 7b204c7b9a005b1b715c278da0d24b219e5fdb83de882f06aef8bf8ce6d1d75b
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