Instructions to use J-Douglas/pixel-character-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use J-Douglas/pixel-character-lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-1", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("J-Douglas/pixel-character-lora") 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-4500/pytorch_model.bin from J-Douglas/pixel-character-lora: direct link, hf CLI and curl.
- Browser
- Download file 3.29 MB
-
https://huggingface.co/J-Douglas/pixel-character-lora/resolve/main/checkpoint-4500/pytorch_model.bin
- Command line
-
hf download hf://J-Douglas/pixel-character-lora/checkpoint-4500/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/J-Douglas/pixel-character-lora/resolve/main/checkpoint-4500/pytorch_model.bin
3.29 MB
- Xet hash:
- d3a2b26be9df70b8f6b368224ffa555adadf83ee635d22711ab503d4df1631f0
- Size of remote file:
- 3.29 MB
- SHA256:
- 52c233c026adfc4e391013ccffb919a012c104fc9eaf114af8758d153a424abb
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