SAFMN Super-Resolution (GGUF)
4x image super-resolution via SAFMN (ICCV 2023). 228K params, 948 KB.
Architecture: Conv3x3 → 8 AttBlocks (SAFM + CCM) → Conv3x3 + PixelShuffle(4).
Parity: cos=1.000000 vs Python reference.
Source: sunny2109/SAFMN (Apache-2.0). Trained on DF2K dataset.
| File | Size | Description |
|---|---|---|
| safmn-x4-f32.gguf | 948 KB | F32, 228K params, 4x upscale |
Provenance and EU AI Act Art. 53 note
- Upstream model: sunny2109/SAFMN.
- Upstream licence:
apache-2.0. This repository redistributes under the same terms; it grants no rights the upstream licence does not. - What was done here: format conversion and/or quantisation only (GGUF). No training, no fine-tuning, no merging, no distillation, no change to architecture, vocabulary or capability. Only the numeric representation of the upstream weights differs.
- Training data: documented — where it is documented at all — by the upstream provider; see the upstream model card. No training data was used, added or selected by this repository.
- Provider status: under Regulation (EU) 2024/1689 the upstream authors remain the provider of this model. Converting the serialisation format does not make this repository the provider of a new general-purpose AI model, and no such claim is made. Questions about training content, copyright policy or model capability belong upstream.
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