Instructions to use rrw23/pets5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rrw23/pets5 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/pets5") 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-500/optimizer.bin from rrw23/pets5: direct link, hf CLI and curl.
- Browser
- Download file 6.59 MB
-
https://huggingface.co/rrw23/pets5/resolve/main/checkpoint-500/optimizer.bin
- Command line
-
hf download hf://rrw23/pets5/checkpoint-500/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/rrw23/pets5/resolve/main/checkpoint-500/optimizer.bin
6.59 MB
- Xet hash:
- b233cc23dc4f49dbdf7b9fe3657aae1c8882181b5f2dcac59b97408af780cf55
- Size of remote file:
- 6.59 MB
- SHA256:
- e59a63ec2d3349d6dae4ebfbb1d3c70ec4f61f3545f39865522d9cb4d701caee
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