
This model is a latent diffusion model for unconditional image generation of mammograms of size 512vs512.
The model was trained with 1000 images using the [DDPM](https://arxiv.org/abs/2006.11239) architecture.
The model was trained for 50 epochs with a batch size of 8 and gradient accumulation of 4, using around 9 GB of GPU memory. 

## Usage

```python
from diffusers import DDPMPipeline

pipeline = DDPMPipeline.from_pretrained({hub_model_id})
image = pipeline().images[0]
image
```

{"license": "mit", "tags": ["pytorch", "diffusers", "unconditional-image-generation", "diffusion-models-class"]}
diffusers pytorch unconditional-image-generation diffusion-models-class arxiv:2006.11239 license:mit diffusers:DDPMPipeline region:us
TAGS
#diffusers #pytorch #unconditional-image-generation #diffusion-models-class #arxiv-2006.11239 #license-mit #diffusers-DDPMPipeline #region-us 


This model is a latent diffusion model for unconditional image generation of mammograms of size 512vs512.
The model was trained with 1000 images using the DDPM architecture.
The model was trained for 50 epochs with a batch size of 8 and gradient accumulation of 4, using around 9 GB of GPU memory. 

## Usage



## Usage
TAGS
#diffusers #pytorch #unconditional-image-generation #diffusion-models-class #arxiv-2006.11239 #license-mit #diffusers-DDPMPipeline #region-us 
 ## Usage