Instructions to use rrw23/pets3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rrw23/pets3 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/pets3") 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-6000/optimizer.bin from rrw23/pets3: direct link, hf CLI and curl.
- Browser
- Download file 6.59 MB
-
https://huggingface.co/rrw23/pets3/resolve/main/checkpoint-6000/optimizer.bin
- Command line
-
hf download hf://rrw23/pets3/checkpoint-6000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/rrw23/pets3/resolve/main/checkpoint-6000/optimizer.bin
6.59 MB
- Xet hash:
- 5af509765a8a8bbf9c642cf0189a925e1528f8f164d00276d3fc07687cbdefe5
- Size of remote file:
- 6.59 MB
- SHA256:
- 2ab5d4539e2467a62e8d8fabc551d78c99c9e5ff21c049e7d4b7fc2221c6dcd9
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