Instructions to use rishabh063/lora-trained-xl-flag with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rishabh063/lora-trained-xl-flag 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("rishabh063/lora-trained-xl-flag") prompt = "a photo of ininin flag" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from rishabh063/lora-trained-xl-flag: direct link, hf CLI and curl.
- Browser
- Download file 635 Bytes
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https://huggingface.co/rishabh063/lora-trained-xl-flag/resolve/main/README.md
- Command line
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hf download hf://rishabh063/lora-trained-xl-flag/README.md
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curl -L -o README.md https://huggingface.co/rishabh063/lora-trained-xl-flag/resolve/main/README.md
635 Bytes
| license: openrail++ | |
| base_model: stabilityai/stable-diffusion-xl-base-1.0 | |
| instance_prompt: a photo of ininin flag | |
| tags: | |
| - stable-diffusion-xl | |
| - stable-diffusion-xl-diffusers | |
| - text-to-image | |
| - diffusers | |
| - lora | |
| inference: true | |
| # LoRA DreamBooth - rishabh063/lora-trained-xl-flag | |
| These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0. The weights were trained on a photo of ininin flag using [DreamBooth](https://dreambooth.github.io/). You can find some example images in the following. | |
| LoRA for the text encoder was enabled: False. | |
| Special VAE used for training: madebyollin/sdxl-vae-fp16-fix. | |