Instructions to use angshineee/dogs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use angshineee/dogs 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("angshineee/dogs") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- d98b10be06c0f36ffdf5133f7ce4d78b8738503410e6015dd834d88f685b98f5
- Size of remote file:
- 6.59 MB
- SHA256:
- 381232117aaaa1ec0d1715d47030f2c52db230ff34f9149537872f67e53f6dc1
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