metadata

license: other
license_name: bespoke-lora-trained-license
license_link: >-
  https://multimodal.art/civitai-licenses?allowNoCredit=False&allowCommercialUse=1&allowDerivatives=False&allowDifferentLicense=False
tags:
  - text-to-image
  - stable-diffusion
  - lora
  - diffusers
  - template:sd-lora
  - migrated
  - retro
  - 1980s
  - actress
  - celebrity
  - juliannejames
base_model: runwayml/stable-diffusion-v1-5
instance_prompt: JulianneJames
widget:
  - text: ' '
    output:
      url: 6433457.jpeg
  - text: ' '
    output:
      url: 6433501.jpeg
  - text: ' '
    output:
      url: 6433502.jpeg
  - text: ' '
    output:
      url: 6433661.jpeg
  - text: ' '
    output:
      url: 6433505.jpeg
  - text: ' '
    output:
      url: 6433659.jpeg
  - text: ' '
    output:
      url: 6433664.jpeg

Julianne James

Model description

This model is made based off of the Adult actress JulianneJames.

Recommend just keeping the LoRa weight at [.8 to 1]

Going above this tends to have the model lean into a handful of the pictures in the data set too heavily for some reason and the hair tends to get very colorful.

experiment to your hearts content.

All of the example photos are created using my own custom models. You can find some here on civitAI including darkglow and some are on my hugging face account. Some of those models are specifically made for the DiffusionBee file format Specifically.

Trigger words

You should use JulianneJames 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('runwayml/stable-diffusion-v1-5', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('brushpenbob/julianne-james', weight_name='JulianneJames.safetensors')
image = pipeline('`JulianneJames`').images[0]

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