README.md

---
license: creativeml-openrail-m
base_model: stabilityai/stable-diffusion-2-base
datasets:
- 'OASIS-3'
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
inference: true
---
    
# Text-to-image finetuning - yurman/mri_full_512_v2_base

This pipeline was finetuned from **stabilityai/stable-diffusion-2-base**
on the **OASIS-3** dataset for brain image generation.
Below are some example images generated with the finetuned pipeline: 

![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("yurman/mri_full_512_v2_base", torch_dtype=torch.float16)
prompt = "An empty, flat black image with a MRI brain axial scan in the center"
image = pipeline(prompt).images[0]
image.save("my_image.png")
```

## Training info

These are the key hyperparameters used during training:

* Epochs: 6
* Learning rate: 0.0001
* embeds rate: 0.0001
* Batch size: 8
* Gradient accumulation steps: 4
* Image resolution: 512
* Mixed-precision: None