| 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']) | |
| ``` | |