Instructions to use rrw23/pets with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rrw23/pets 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("rrw23/pets") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- f60f1f03118e14a4a885f07e528651a06e6c128019e262ab2b8e4710b81097c5
- Size of remote file:
- 6.59 MB
- SHA256:
- 6d587064cdebd44e0aaaaa93d6ae186e032b5b4ceb982c919529b763e0613512
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