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:
- 2c97249f52d063b74786d3b456824db58216ea20b3e78cd3ca71b55145e97ad6
- Size of remote file:
- 3.4 MB
- SHA256:
- 247c1a1de3b826a57542c3d56e1ca8c10dc9d74682cb5cad033bb9f8fd271b96
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