This pipeline was finetuned from kandinsky-community/kandinsky-2-2-decoder on the ChoudharyTAlhaArain/web-kadi-2.0 dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['update web ui/ux']:

Pipeline usage

You can use the pipeline like so:

python

from diffusers import DiffusionPipeline
import torch

pipeline = AutoPipelineForText2Image.from_pretrained("ChoudharyTAlhaArain/kadsinky-web-decoder-3.0", torch_dtype=torch.float16)
prompt = "update web ui/ux"
image = pipeline(prompt).images[0]
image.save("my_image.png")

Training info

These are the key hyperparameters used during training:

Epochs: 12
Learning rate: 1e-05
Batch size: 1
Gradient accumulation steps: 4
Image resolution: 512
Mixed-precision: None

More information on all the CLI arguments and the environment are available on your wandb run page.