Instructions to use sselpah/pe51illust-sih-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use sselpah/pe51illust-sih-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("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("sselpah/pe51illust-sih-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
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Download README.md from sselpah/pe51illust-sih-lora: direct link, hf CLI and curl.
- Browser
- Download file 376 Bytes
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https://huggingface.co/sselpah/pe51illust-sih-lora/resolve/main/README.md
- Command line
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hf download hf://sselpah/pe51illust-sih-lora/README.md
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curl -L -o README.md https://huggingface.co/sselpah/pe51illust-sih-lora/resolve/main/README.md
376 Bytes
metadata
license: apache-2.0
tags:
- lora
- noob
- safetensors
- diffusers
DISCLAIMER:
i suck at lora training, good luck
lora trained on SIH noob base (vpred)
style: pe51illust
image count: 132
trigger word (i dont know if this helps): 51pe
tips:
use paint_splatter
to change paint_splatter color try to write just color names like blue, orange, yellow as tags