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yurman/
uncond-sd2-base-complex-4

Name: uncond-sd2-base-complex-4
Availability: InStock

diffusers

safetensors

stable-diffusion

stable-diffusion-diffusers

yurman/uncond_sd2-base

finetune

creativeml-openrail-m

StableDiffusionUnconditionalPipeline

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Unconditioned stable diffusion finetuning - yurman/uncond-sd2-base-complex-4

This pipeline was finetuned from yurman/uncond_sd2-base for brain image generation. Below are some example images generated with the finetuned pipeline:

Pipeline usage

You can use the pipeline like so:

python

from diffusers import StableDiffusionUnconditionalPipeline
import torch

pipeline = StableDiffusionUnconditionalPipeline.from_pretrained("yurman/uncond-sd2-base-complex-4", torch_dtype=torch.float32)
image = pipeline(1).images[0]
image.save("brain_image.png")

Training info

These are the key hyperparameters used during training:

Epochs: 400
Max Train Steps: 100000
Learning rate: 5e-05
Batch size: 18
VAE scaling: 0.12
VAE type: MEDVAE
Input perturbation: 0.0
Noise offset: 0.0
Gradient accumulation steps: 3
Image resolution: 256
Mixed-precision: no
Max rotation degree: 10
Prediction Type: v_prediction
SNR Gamma: 5.0

More information on all the CLI arguments and the environment are available on your wandb run page.