Instructions to use rrw23/pets10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rrw23/pets10 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/pets10") 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-3000/optimizer.bin from rrw23/pets10: direct link, hf CLI and curl.
- Browser
- Download file 6.59 MB
-
https://huggingface.co/rrw23/pets10/resolve/main/checkpoint-3000/optimizer.bin
- Command line
-
hf download hf://rrw23/pets10/checkpoint-3000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/rrw23/pets10/resolve/main/checkpoint-3000/optimizer.bin
6.59 MB
- Xet hash:
- 114cfba10046879a57f95f696bc6bd72a199cda1ed3cc6d1a0c5711b826948fb
- Size of remote file:
- 6.59 MB
- SHA256:
- dc4e7c361a8ba13498a232d5d52763195b445e99fed7a4d8983995d985600888
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