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:

Pipeline usage

You can use the pipeline like so:

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