
This is a latent diffusion model for generation of mammograms with size 64x64 in the latent space.
It was trained with 4K images in the latent space (10% of the original dataset) for 50 epochs.
Images in the latent space have size (4,64,64) and can generate images of 512x512 when decoded using the VAE. 

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


This is a latent diffusion model for generation of mammograms with size 64x64 in the latent space.
It was trained with 4K images in the latent space (10% of the original dataset) for 50 epochs.
Images in the latent space have size (4,64,64) and can generate images of 512x512 when decoded using the VAE. 

## Usage



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