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:
- f9c35b570004422285198e78ec348f41ee8cc8f360fb9272e45600cdc53e44f1
- Size of remote file:
- 3.29 MB
- SHA256:
- a449b87e72eb79f58790ea05952ff405dd525027ed9b4b5e2b487aebe2c99314
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