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Text-to-image finetuning - peterholdsworth/output2

This pipeline was finetuned from CompVis/stable-diffusion-v1-2 on the peterholdsworth/AND dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['Please draw a mug with an ANDlogo logo']:

val_imgs_grid

Pipeline usage

You can use the pipeline like so:

from diffusers import DiffusionPipeline
import torch

pipeline = DiffusionPipeline.from_pretrained("peterholdsworth/output2", torch_dtype=torch.float16)
prompt = "Please draw a mug with an ANDlogo logo"
image = pipeline(prompt).images[0]
image.save("my_image.png")

Training info

These are the key hyperparameters used during training:

  • Epochs: 400
  • Learning rate: 1e-05
  • Batch size: 1
  • Gradient accumulation steps: 4
  • Image resolution: 512
  • Mixed-precision: fp16
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Dataset used to train peterholdsworth/output2