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 Settings
- Draw Things
- DiffusionBee
Download checkpoint-10500/pytorch_model.bin from rrw23/pets: direct link, hf CLI and curl.
- Browser
- Download file 3.29 MB
-
https://huggingface.co/rrw23/pets/resolve/main/checkpoint-10500/pytorch_model.bin
- Command line
-
hf download hf://rrw23/pets/checkpoint-10500/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/rrw23/pets/resolve/main/checkpoint-10500/pytorch_model.bin
3.29 MB
- Xet hash:
- a71207355647e38c1d9fbe8fba798b828b7be1b6885e3c5943c2f2a8ccd3af2e
- Size of remote file:
- 3.29 MB
- SHA256:
- d84d2cc53337b67b8c3dac8d37fda957866eef07867718fb76673f1d279f40b9
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