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']: | |
![val_imgs_grid](./val_imgs_grid.png) | |
## 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: 50 | |
* Learning rate: 1e-05 | |
* Batch size: 2 | |
* Image resolution: 512 | |
* Mixed-precision: fp16 | |