Instructions to use rrw23/pets9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rrw23/pets9 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/pets9") 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:
- 3fac35b28ca07f94b014e78a241f8e23df711dd8c47ec78b9be44ae0fe6bda21
- Size of remote file:
- 6.59 MB
- SHA256:
- a163ce9f8fb7102899415ec22d149c5d3e78da8cb5910ae79765a6a123c42c83
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