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library_name: pytorch
license: cc-by-nc-4.0
tags:
- super-resolution
- latent-diffusion
- pytorch
- rocm
- research
---
# sr-diffusion
Research checkpoint storage for the `sr-diffusion` project.
GitHub: https://github.com/BitIntx/sr-diffusion
This is a public source-available, non-commercial research project. It trains a
vision-only x4 latent diffusion super-resolution pipeline from scratch and does
not use a pretrained text-to-image diffusion model.
Current artifacts are study/research checkpoints. They are not a production SR
model.
## License
- Checkpoints, generated samples, metrics, and other non-code artifacts:
CC BY-NC 4.0.
- Source code: PolyForm Noncommercial License 1.0.0.
Commercial use is not permitted without separate written permission. This
includes paid hosted inference, resale, and integration into commercial
products.
Training data is not redistributed in this repository. Dataset license
constraints should be reviewed before training or redistributing derived
weights.
## Artifacts
| Path | Source | SHA256 |
| --- | --- | --- |
| `LICENSE` | `LICENSE` | `c635a1fa2c80` |
| `CHECKPOINT_LICENSE.md` | `CHECKPOINT_LICENSE.md` | `da3b25759abb` |
| `configs/diffusion_photo10k_b32.yaml` | `diffusion_photo10k_b32.yaml` | `0fa6c0eeec85` |
| `checkpoints/stage3_diffusion_b32_best_eval_noise.pt` | `best_eval_noise.pt` | `ea4b458d668c` |
| `checkpoints/stage3_diffusion_b32_step_0025000.pt` | `step_0025000.pt` | `38d2f44adf65` |
| `metrics/stage3_b32_step_0024000_metrics.json` | `step_0024000_metrics.json` | `7df33601c289` |
| `metrics/stage3_b32_step_0025000_metrics.json` | `step_0025000_metrics.json` | `bebb82e594da` |
## Stages
- Stage 1: factor-4 VAE / Autoencoder over 512px HR crops.
- Stage 2: deterministic LR-to-HR-latent pretraining with the Stage 1 VAE frozen.
- Stage 3: conditional latent diffusion U-Net, planned.
|