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: 100
- Learning rate: 5e-06
- Batch size: 2
- Image resolution: 512
- Mixed-precision: fp16