Instructions to use lora-library/https-huggingface-co-lora-library-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lora-library/https-huggingface-co-lora-library-test 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-2-1-base", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("lora-library/https-huggingface-co-lora-library-test") prompt = "Ping hair" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from lora-library/https-huggingface-co-lora-library-test: direct link, hf CLI and curl.
- Browser
- Download file 713 Bytes
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https://huggingface.co/lora-library/https-huggingface-co-lora-library-test/resolve/main/README.md
- Command line
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hf download hf://lora-library/https-huggingface-co-lora-library-test/README.md
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curl -L -o README.md https://huggingface.co/lora-library/https-huggingface-co-lora-library-test/resolve/main/README.md
713 Bytes
| license: creativeml-openrail-m | |
| base_model: stabilityai/stable-diffusion-2-1-base | |
| instance_prompt: Ping hair | |
| tags: | |
| - stable-diffusion | |
| - stable-diffusion-diffusers | |
| - text-to-image | |
| - diffusers | |
| - lora | |
| inference: true | |
| # LoRA DreamBooth - bo | |
| These are LoRA adaption weights for [stabilityai/stable-diffusion-2-1-base](https://huggingface.co/stabilityai/stable-diffusion-2-1-base). The weights were trained on the instance prompt "Ping hair " using [DreamBooth](https://dreambooth.github.io/). You can find some example images in the following. | |
| Test prompt: Ping | |
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