metadata

license: creativeml-openrail-m
base_model: runwayml/stable-diffusion-v1-5
datasets:
  - Drozdik/tattoo_v3
tags:
  - stable-diffusion
  - stable-diffusion-diffusers
  - text-to-image
  - diffusers
inference: true

Text-to-image finetuning - TejasNavada/tattoo-diffusion

This pipeline was finetuned from runwayml/stable-diffusion-v1-5 on the Drozdik/tattoo_v3 dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['a dragon on a white background', ' a fiery skull', 'a skull', 'a face', 'a snake and skull']:

Pipeline usage

You can use the pipeline like so:

from diffusers import DiffusionPipeline
import torch

pipeline = DiffusionPipeline.from_pretrained("TejasNavada/tattoo-diffusion", torch_dtype=torch.float16)
prompt = "a dragon on a white background"
image = pipeline(prompt).images[0]
image.save("my_image.png")

Training info

These are the key hyperparameters used during training:

Epochs: 50
Learning rate: 1e-05
Batch size: 2
Image resolution: 512
Mixed-precision: fp16