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Open-weight model · Image to image

sr_decoder_iclr

by Raesr Research raesrreseach/sr_decoder_iclr

sr_decoder_iclr is an open-weight model for image to image from Raesr Research, released under Creative Commons Attribution-NonCommercial 4.0. Its published files total 1.9 GB.

Release package for the paper's single-pass super-resolution models: Both models follow the paper protocol: RGB image → bicubic resize to 512×512 → one forward pass → mean-only color matching in the float domain, before PNG quantization: per RGB channel…

Parameters—
Context—
Weights1.9 GB
Licensecc-by-nc-4.0
AccessOpen weights
Monthly Downloads—

Model Card

Release package for the paper's single-pass super-resolution models: Both models follow the paper protocol: RGB image → bicubic resize to 512×512 → one forward pass → mean-only color matching in the float domain, before PNG quantization: per RGB channel, clamp(sr - mean(sr,H,W) + mean(lr,H,W), 0, 1), where lr is the same 512×512 bicubic-resized tensor the model consumed. The formula is recorded in every run manifest. There is no hidden color alignment, post-processing, normalization, or implicit fallback model. The released RAESR decoder is the paper's Stage 3, seed 42, step-600 EMA checkpoint: The encoder layers are named 0-indexed in code and manifests (layers 1..23 for RAESR, layers…

Excerpt from the card by Raesr Research, licensed cc-by-nc-4.0.

Identity and Version

Repository
raesrreseach/sr_decoder_iclr
Publisher
Raesr Research
Task
Image to image
Modality
Image
Library
Not stated by the source
Parameters
Not stated by the source
Languages
Not stated by the source
Revision
45d3d29ba2ce1794dd94224ffa7c21512ad955cb
First published
2026-09-24
Last updated
2026-09-26

Files and Weights

39 files, 1.9 GB in total. The weights are 2 files totalling 1.9 GB in pt.

Weights2 files · 1.9 GB
Configuration30 files · 192.2 KB
Documentation4 files · 19.1 KB
Other2 files · 469 B
Repository1 file · 1.5 KB
Every file
FileTypeSizeSHA-256
ema_decoder.ptWeights1.7 GB 2e4de5df2461
weights/raesr_d_frontend.ptWeights231.2 MB 72f970fc9366
benchmark/__init__.pyConfiguration67 B —
benchmark/run_raesr_benchmark.pyConfiguration13.1 KB —
benchmark/score.pyConfiguration8.5 KB —
benchmark/summarize.pyConfiguration4.8 KB —
benchmark/tests/test_paper_provenance.pyConfiguration12.2 KB —
benchmark/validate_outputs.pyConfiguration2.2 KB —
benchmark/verify_paper_reproduction.pyConfiguration22.6 KB —
environment/environment.ymlConfiguration286 B —
manifests/model_artifacts.jsonConfiguration1.6 KB —
manifests/paper_reference_metrics.jsonConfiguration3.0 KB —
manifests/paper_reference_metrics_raesr_d.jsonConfiguration3.1 KB —
manifests/runtime_provenance.jsonConfiguration3.3 KB —
raesr/__init__.pyConfiguration218 B —
raesr/artifacts.pyConfiguration7.6 KB —
raesr/runtime/__init__.pyConfiguration187 B —
raesr/runtime/configs/decoder/ViTXL/config.jsonConfiguration735 B —
raesr/runtime/decoder_rope.pyConfiguration28.7 KB —
raesr/runtime/encoders/__init__.pyConfiguration197 B —
raesr/runtime/encoders/models/__init__.pyConfiguration63 B —
raesr/runtime/encoders/models/dinov3_loader.pyConfiguration2.5 KB —
raesr/runtime/encoders/vision_encoder.pyConfiguration41.9 KB —
raesr/runtime/frontends/__init__.pyConfiguration50 B —
raesr/runtime/frontends/raesr_d.pyConfiguration7.3 KB —
raesr/runtime/rae_rope.pyConfiguration9.7 KB —
scripts/__init__.pyConfiguration45 B —
scripts/download_artifacts.pyConfiguration1.6 KB —
scripts/infer.pyConfiguration7.5 KB —
scripts/smoke_test.pyConfiguration3.0 KB —
scripts/test_infer.pyConfiguration4.6 KB —
scripts/verify_artifacts.pyConfiguration1.8 KB —
LICENSEDocumentation544 B —
README.mdDocumentation8.9 KB —
THIRD_PARTY_NOTICES.mdDocumentation1.9 KB —
docs/REPRODUCIBILITY.mdDocumentation7.7 KB —
environment/requirements-metrics.txtOther175 B —
environment/requirements-runtime.txtOther294 B —
.gitattributesRepository1.5 KB —

License and Download

License
cc-by-nc-4.0
Access
Open weights, no gate
Download size
1.9 GB
Download from Raesr Research

Released by Raesr Research through its official repository on Hugging Face. Read the license.

Memory Requirements

PrecisionWeights in memory
As published1.9 GB

Weights only, from the published parameter count; the key-value cache and runtime add to this.

Questions About sr_decoder_iclr

Can I use sr_decoder_iclr commercially?

Not without separate permission. sr_decoder_iclr is released under Creative Commons Attribution-NonCommercial 4.0. CC BY-NC 4.0 permits sharing and adapting with credit for non-commercial purposes only. Commercial use needs separate permission from the rights holder.

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