| # latent-diffusion-autoencoder-128 | |
| This is a PyTorch checkpoint for a Latent Diffusion model. | |
| ## Model Details | |
| - **Checkpoint file**: `100000.pth` | |
| - **File size**: 3086.4 MB | |
| - **Framework**: PyTorch | |
| - **Model type**: Latent Diffusion Autoencoder | |
| ## Usage | |
| ```python | |
| import torch | |
| from huggingface_hub import hf_hub_download | |
| # Download the checkpoint | |
| checkpoint_path = hf_hub_download( | |
| repo_id="YOUR_USERNAME/latent-diffusion-autoencoder-128", | |
| filename="100000.pth" | |
| ) | |
| # Load the checkpoint | |
| checkpoint = torch.load(checkpoint_path, map_location='cpu') | |
| print("Checkpoint keys:", list(checkpoint.keys())) | |
| ``` | |
| ## Training Details | |
| - **Dataset**: OpenWebText-512 | |
| - **Latent dimensions**: 128 | |
| - **Training steps**: 100,000 | |
| ## Citation | |
| If you use this model, please cite the original Latent Diffusion paper and this checkpoint. | |