--- license: other license_name: bespoke-lora-trained-license license_link: https://multimodal.art/civitai-licenses?allowNoCredit=True&allowCommercialUse=Rent&allowDerivatives=True&allowDifferentLicense=False tags: - text-to-image - stable-diffusion - lora - diffusers - template:sd-lora - lineart - vector - simple - style - vector-art - vector art - complex - vector illustration - vector style base_model: stabilityai/stable-diffusion-xl-base-1.0 instance_prompt: vector widget: - text: ' ' output: url: >- 3823589.jpeg - text: ' ' output: url: >- 3823606.jpeg - text: ' ' output: url: >- 3822700.jpeg - text: ' ' output: url: >- 3822702.jpeg - text: ' ' output: url: >- 3823587.jpeg - text: ' ' output: url: >- 3822063.jpeg - text: ' ' output: url: >- 3823818.jpeg - text: ' ' output: url: >- 3823823.jpeg - text: ' ' output: url: >- 3823826.jpeg - text: ' ' output: url: >- 3823850.jpeg --- # Doctor Diffusion's Controllable Vector Art XL LoRA ## Model description

This LoRA was trained exclusively on modified and captioned CC0/Pubic Domain images by myself!

USE: "vector" with v2
or
"vctr artstyle" with v1


You can control the level of detail and type of vector art and if there are outlines with these prompts:

For color results use:
"simple details"
"complex details"
"outlines"
"solid color background"

For black and white line art use:
"black line art"
"white background"

## Trigger words You should use `vector` to trigger the image generation. ## Download model Weights for this model are available in Safetensors format. [Download](/DoctorDiffusion/doctor-diffusion-s-controllable-vector-art-xl-lora/tree/main) them in the Files & versions tab. ## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers) ```py from diffusers import AutoPipelineForText2Image import torch pipeline = AutoPipelineForText2Image.from_pretrained('stabilityai/stable-diffusion-xl-base-1.0', torch_dtype=torch.float16).to('cuda') pipeline.load_lora_weights('DoctorDiffusion/doctor-diffusion-s-controllable-vector-art-xl-lora', weight_name='DD-vector-v2.safetensors') image = pipeline('`vector`').images[0] ``` For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)