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-12500/optimizer.bin from rrw23/pets: direct link, hf CLI and curl.
- Browser
- Download file 6.59 MB
-
https://huggingface.co/rrw23/pets/resolve/main/checkpoint-12500/optimizer.bin
- Command line
-
hf download hf://rrw23/pets/checkpoint-12500/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/rrw23/pets/resolve/main/checkpoint-12500/optimizer.bin
6.59 MB
- Xet hash:
- 20c063201225a76549418c80ca84d7c21ca6b7418204fcb681695a454b73d01b
- Size of remote file:
- 6.59 MB
- SHA256:
- d2e068cc85e16d9305d5e8bb157025aead1b1434adedd33f70d368ddc1ba429c
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