metadata

base_model: stabilityai/stable-diffusion-xl-base-1.0
library_name: diffusers
license: creativeml-openrail-m
tags:
  - stable-diffusion-xl
  - stable-diffusion-xl-diffusers
  - text-to-image
  - diffusers
  - diffusers-training
  - lora
inference: true
widget:
  - text: monet,  a landscape of a snowy mountain region big clouds
    output:
      url: images/example_ul824c994.png
  - text: >-
      monet, majestic cliffs overlooking a serene ocean, with dramatic rock
      formations bathed in soft light. The cliffs are painted in shades of
      green, ochre, and brown, contrasting with the smooth, flowing waves below,
      capturing the raw, natural beauty of the landscape
    output:
      url: images/example_kuktgiadt.png
  - text: >-
      monet,  mountains far back, street lamps shines with warm yellow colors,
      black night
    output:
      url: images/example_k3nlagsga.png
  - text: Monet garden scene with colorful flowers and reflections on water
    output:
      url: images/example_r2xalzxv0.png
  - text: Monet snowy lakeside at sunset
    output:
      url: images/example_eztpwthdj.png
datasets:
  - Aedancodes/monet_dataset

LoRA text2image fine-tuning

These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0. The weights were fine-tuned on the Aedancodes/monet_dataset dataset.

Trigger words

Trigger words: You should use Monet to trigger the image generation.

Training details

resolution=1024*1024
train batch_size = 1
max train steps = 1000
learning rate = 5e-5
lr scheduler = constant
mixed precision = fp16
8bit_adam