---
library_name: ired
tags:
- autoencoder
- bart
- latent-diffusion
---

# IRED Autoencoder — `roy-W/ired-reasoning`

Frozen BART autoencoder with compression/reconstruction split.

- **Pool type:** `conv`
- **Latent slots (K):** 384
- **d_ae:** 768
- **Decoder fine-tuned:** yes
- **Base model:** `facebook/bart-base`
- **Training steps:** 5

## Usage

```python
from ired.model.autoencoder import FrozenBartAutoencoder
import torch

ae = FrozenBartAutoencoder(
    model_name='facebook/bart-base',
    k=384,
    pool_type='conv',
    d_ae=768,
    train_decoder=True,
)
ckpt = torch.load('ae_checkpoint.pt', map_location='cpu')
ae.load_ae(ckpt['ae'])
```