doctor-diffusion-s-controllable-vector-art-xl-lora

Doctor Diffusion's Controllable Vector Art XL LoRA

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Model description

<p>This LoRA was trained exclusively on modified and captioned CC0/Pubic Domain images by myself! <br /><br />USE: "<strong>vector</strong>" with v2<br />or<br />"<strong>vctr artstyle</strong>" with v1</p><p><br /><strong><span style="color:rgb(219, 222, 225)">You can control the level of detail and type of vector art and if there are outlines with these prompts: </span></strong><br /><br />For <strong>color results</strong> use:<br />"<strong>simple</strong> details"<br />"<strong>complex </strong>details"<br />"<strong>outlines</strong>"<br />"solid color background"<br /><br />For <strong>black and white line art</strong> use:<br />"<strong>black line art</strong>"<br />"white background"<br /></p>

Trigger words

You should use vector to trigger the image generation.

Download model

Weights for this model are available in Safetensors format.

Download them in the Files & versions tab.

Use it with the 🧨 diffusers library

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