| # Reproducibility Notes | |
| ## Checkpoint Conversion | |
| The released files were converted from training checkpoints with: | |
| ```python | |
| ckpt = torch.load("final.pt", map_location="cpu") | |
| state = {k.removeprefix("module."): v.detach().cpu().contiguous() for k, v in ckpt["model"].items()} | |
| safetensors.torch.save_file(state, "model.safetensors") | |
| ``` | |
| The original `.pt` files contain optimizer and training state. The released | |
| `.safetensors` files contain only the model state dict required for inference. | |
| ## Verification | |
| Each converted checkpoint was reloaded with `safetensors.torch.load_file`, and | |
| the tensor key set was checked against the source PyTorch checkpoint. A forward | |
| pass sanity check was also run using the TeX-1500 codebase and a synthetic | |
| `[1, 64, 64, 64]` HSI tensor. | |
| ## Data Access | |
| The TeX-1500 dataset is gated on Hugging Face. Users need to log in and accept | |
| the dataset access conditions before downloading samples for reproduction. | |