AhmetTek41/kandinskytest

Finetuning - AhmetTek41/output

This pipeline was finetuned from kandinsky-community/kandinsky-2-2-decoder on the AhmetTek41/logo dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['A logo for a zero waste club featuring a simple image of a closed loop of arrows, with each arrow made from different recyclable materials like paper, plastic, and metal.']:

Pipeline usage

You can use the pipeline like so:

from diffusers import DiffusionPipeline
import torch

pipeline = AutoPipelineForText2Image.from_pretrained("AhmetTek41/output", torch_dtype=torch.float16)
prompt = "A logo for a zero waste club featuring a simple image of a closed loop of arrows, with each arrow made from different recyclable materials like paper, plastic, and metal."
image = pipeline(prompt).images[0]
image.save("my_image.png")

Training info

These are the key hyperparameters used during training:

• Epochs: 77
• Learning rate: 1e-05
• Batch size: 16
• Gradient accumulation steps: 1
• Image resolution: 512
• Mixed-precision: None

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