metadata

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
  - negative
  - detail
  - tool
  - negative lora
  - quality up
  - improvement
base_model: stabilityai/stable-diffusion-xl-base-1.0
instance_prompt: null
widget:
  - text: painting of flowers on a table in the sun
    output:
      url: 3339543.jpeg
  - text: ' '
    output:
      url: 3339545.jpeg
  - text: ' '
    output:
      url: 3339570.jpeg
  - text: ' '
    output:
      url: 3339566.jpeg
  - text: ' '
    output:
      url: 3339563.jpeg
  - text: ' '
    output:
      url: 3339565.jpeg
  - text: ' '
    output:
      url: 3339564.jpeg
  - text: ' '
    output:
      url: 3339569.jpeg
  - text: ' '
    output:
      url: 3339568.jpeg
  - text: ' '
    output:
      url: 3339567.jpeg

Doctor Diffusion's Negative XL LoRA

Prompt
painting of flowers on a table in the sun

Model description

Increate the quality and amount of details with this negative XL LoRA.

THIS IS MEANT TO BE USED WITH NEGATIVE STRENGHT VALUES.

An updated version my "point-e" negative embedding for use with XL.

Keep CLIP strength at 1.0 and adjust the strength of the LoRA to preference.

LoRA Strength can range from -0.01 to -2.00.

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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-negative-xl-lora', weight_name='DD-pnte-neg-v1.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