Downloads · 30 days
64
1% of all-time downloads
uncond-sd2-base-complex-4
yurman/uncond-sd2-base-complex-4
uncond-sd2-base-complex-4 is a machine learning model from yurman. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for diffusers. The card lists the license as creativeml-openrail-m.
This pipeline was finetuned from yurman/uncondsd2-base for brain image generation. Below are some example images generated with the finetuned pipeline:
All-time downloads
4.9K
Public
Parameters
816M
16.5 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors10 GB · 61%
At a glance
- Library
- diffusers
- License
- creativeml-openrail-m
- Access
- Public
- Created
- Jul 1, 2025
- Updated
- Feb 16, 2026
- SHA
- 5c181138
Base models
Model card
From the Hugging Face model README
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:
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.
- Library
- diffusers
- License
- creativeml-openrail-m
- Created
- Jul 1, 2025
- Updated
- Feb 16, 2026