Instructions to use shadowalker0123/doski with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use shadowalker0123/doski with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("shadowalker0123/doski") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from shadowalker0123/doski: direct link, hf CLI and curl.
- Browser
- Download file 468 Bytes
-
https://huggingface.co/shadowalker0123/doski/resolve/main/README.md
- Command line
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hf download hf://shadowalker0123/doski/README.md
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curl -L -o README.md https://huggingface.co/shadowalker0123/doski/resolve/main/README.md
468 Bytes
| tags: | |
| - text-to-image | |
| - lora | |
| - diffusers | |
| - template:diffusion-lora | |
| widget: | |
| - output: | |
| url: images/cowboy.jpg | |
| text: '-' | |
| base_model: stabilityai/stable-diffusion-xl-base-1.0 | |
| instance_prompt: dskp | |
| license: apache-2.0 | |
| # doskoinpo | |
| <Gallery /> | |
| ## Model description | |
| Another civit ai | |
| ## Trigger words | |
| You should use `dskp` to trigger the image generation. | |
| ## Download model | |
| [Download](/shadowalker0123/doski/tree/main) them in the Files & versions tab. | |