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
- Draw Things
- DiffusionBee
- Xet hash:
- 3dda8e8237cfe4df5977214b4ce6e297b8cc7cac794a016437b7a21b83c6600a
- Size of remote file:
- 3.29 MB
- SHA256:
- 6c28cf4f7b5af3c0015831d4cd6257118733d3f1045fc4edd146f428e443a199
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