Instructions to use PeterD69/b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use PeterD69/b with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("krea/Krea-2-Raw", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("PeterD69/b") prompt = "A hyper-realistic portrait of a vpx man wearing iridescent neon armor, standing amidst the glowing flora of a bioluminescent alien jungle." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-1000/optimizer.bin from PeterD69/b: direct link, hf CLI and curl.
- Browser
- Download file 195 MB
-
https://huggingface.co/PeterD69/b/resolve/main/checkpoint-1000/optimizer.bin
- Command line
-
hf download hf://PeterD69/b/checkpoint-1000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/PeterD69/b/resolve/main/checkpoint-1000/optimizer.bin
195 MB
- Xet hash:
- 6eeeefd07970da0b796a5f802d72b73443dc26e08ed0189f088ca1c6a6a7c676
- Size of remote file:
- 195 MB
- SHA256:
- 2e4f710ed15ef6a1f104af1f56c194e4a4b2d95944576cc13ba8b2a344781e5c
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