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:
- def68e2a9876f87e74ebaa13c9ae45db02473036df29cc6a6bd75d4d42782678
- Size of remote file:
- 3.4 MB
- SHA256:
- e63fc32bd11f88fdfd7f88ff7ee03893f45ea0827a2b60c08a07a71ce355677a
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