Instructions to use debadas/dog with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use debadas/dog with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("debadas/dog") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- f083f2441959406a6506178d94f39d89efc237ee0099d1dc85f05946a262268d
- Size of remote file:
- 6.59 MB
- SHA256:
- 467350d91a2eab4f4a51e9b9e7d6faf0c65b669e59aabf00d201c9f44ffb1ae1
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