File size: 1,419 Bytes
97cdf26 80ccb99 a40bb25 d2893a6 80ccb99 97cdf26 05e58a2 97cdf26 05e58a2 97cdf26 95e4f94 99f423a 95e4f94 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 |
---
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
---
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# 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.
## Training details
```python
resolution=1024*1024
train batch_size = 1
max train steps = 1000
learning rate = 5e-5
lr scheduler = constant
mixed precision = fp16
8bit_adam
``` |