| 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: | |
| ```python | |
| 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 | |