Instructions to use rrw23/pets6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rrw23/pets6 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/pets6") 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-8500/scheduler.bin from rrw23/pets6: direct link, hf CLI and curl.
- Browser
- Download file 1 kB
-
https://huggingface.co/rrw23/pets6/resolve/main/checkpoint-8500/scheduler.bin
- Command line
-
hf download hf://rrw23/pets6/checkpoint-8500/scheduler.bin
-
curl -L -o scheduler.bin https://huggingface.co/rrw23/pets6/resolve/main/checkpoint-8500/scheduler.bin
1 kB
- Xet hash:
- f87a96bb1fb5abe92f98fc9bb2d81684bd3ec55c44b1297e49fcae07db1e5621
- Size of remote file:
- 1 kB
- SHA256:
- 2127535cd4da03b68a0704900df7f5fcd98afb5851da931f1762e11645c51d79
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