metadata

license: other
license_name: bespoke-lora-trained-license
license_link: >-
  https://multimodal.art/civitai-licenses?allowNoCredit=False&allowCommercialUse=Image&allowDerivatives=True&allowDifferentLicense=True
tags:
  - text-to-image
  - stable-diffusion
  - lora
  - diffusers
  - template:sd-lora
  - migrated
  - anime
  - 3d
  - paper
  - animation
  - style
base_model: stabilityai/stable-diffusion-xl-base-1.0
instance_prompt: null
widget:
  - text: ' '
    output:
      url: 3685307.jpeg
  - text: ' '
    output:
      url: 3684557.jpeg
  - text: ' '
    output:
      url: 3684556.jpeg
  - text: ' '
    output:
      url: 3684558.jpeg
  - text: ' '
    output:
      url: 3684555.jpeg
  - text: ' '
    output:
      url: 3657129.jpeg
  - text: ' '
    output:
      url: 3657131.jpeg
  - text: ' '
    output:
      url: 3657134.jpeg
  - text: ' '
    output:
      url: 3657136.jpeg
  - text: ' '
    output:
      url: 3657138.jpeg
  - text: ' '
    output:
      url: 3657139.jpeg
  - text: ' '
    output:
      url: 3657140.jpeg
  - text: ' '
    output:
      url: 3657141.jpeg
  - text: ' '
    output:
      url: 3657144.jpeg
  - text: ' '
    output:
      url: 3657143.jpeg
  - text: ' '
    output:
      url: 3657142.jpeg
  - text: ' '
    output:
      url: 3657146.jpeg
  - text: ' '
    output:
      url: 3657145.jpeg
  - text: ' '
    output:
      url: 3657148.jpeg
  - text: ' '
    output:
      url: 3657147.jpeg

3D Animation Style SDXL

Model description

None

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('thejagstudio/3d-animation-style-sdxl', weight_name='3D_Animation_Style-000009.safetensors')
image = pipeline('Your custom prompt').images[0]

For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers