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Update Apache-2.0 release audit metadata

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  1. MANIFEST.md +4 -2
  2. RELEASE_AUDIT.md +7 -6
  3. SHA256SUMS +2 -2
MANIFEST.md CHANGED
@@ -1,8 +1,8 @@
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  # BERTose and AFFINose Training-Code Manifest
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- **Updated**: 2026-05-17
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  **Public repository**: `https://huggingface.co/supanthadey1/bertose-affinose-training-code`
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- **Current public contents**: 129 files, approximately 54 MB
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  **Scope**: training, benchmarking, probe, split/vocabulary, and provenance code needed to understand and reproduce the released BERTose and AFFINose workflows.
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  This manifest describes the files actually present in the public Hugging Face training-code repository. Large corpora, intermediate mapping files, checkpoints, generated figures, and full result bundles are intentionally not bundled here; the released checkpoints and inference notebook are linked from the repository README.
@@ -24,6 +24,7 @@ Some executable files keep historical development names so that the code remains
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  | `README.md` | Reviewer/user-facing overview, repository map, checkpoint links, install notes, and quick import check |
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  | `MANIFEST.md` | This file; exact public package map |
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  | `RELEASE_AUDIT.md` | Public-release checks, repaired gaps, verification results, and known scope limits |
 
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  | `requirements.txt` | Core Python dependencies plus optional analysis/probe packages |
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  | `SHA256SUMS` | Checksums for every public file except `SHA256SUMS` itself |
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@@ -100,6 +101,7 @@ The public release was checked by no-token Hugging Face readback. The following
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  - The repository is public and ungated.
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  - The remote file list exactly matches the local staged release.
 
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  - A no-token snapshot download succeeds.
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  - `SHA256SUMS` verifies every downloaded file.
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  - No Hugging Face token-looking strings were found.
 
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  # BERTose and AFFINose Training-Code Manifest
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+ **Updated**: 2026-06-10
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  **Public repository**: `https://huggingface.co/supanthadey1/bertose-affinose-training-code`
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+ **Current public contents**: 130 files, approximately 54 MB
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  **Scope**: training, benchmarking, probe, split/vocabulary, and provenance code needed to understand and reproduce the released BERTose and AFFINose workflows.
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  This manifest describes the files actually present in the public Hugging Face training-code repository. Large corpora, intermediate mapping files, checkpoints, generated figures, and full result bundles are intentionally not bundled here; the released checkpoints and inference notebook are linked from the repository README.
 
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  | `README.md` | Reviewer/user-facing overview, repository map, checkpoint links, install notes, and quick import check |
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  | `MANIFEST.md` | This file; exact public package map |
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  | `RELEASE_AUDIT.md` | Public-release checks, repaired gaps, verification results, and known scope limits |
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+ | `LICENSE` | Apache License 2.0 terms for the BERTose/AFFINose code, notebooks and released model artifacts |
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  | `requirements.txt` | Core Python dependencies plus optional analysis/probe packages |
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  | `SHA256SUMS` | Checksums for every public file except `SHA256SUMS` itself |
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  - The repository is public and ungated.
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  - The remote file list exactly matches the local staged release.
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+ - Model card license metadata is `apache-2.0`, and the repository includes an Apache-2.0 `LICENSE` file.
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  - A no-token snapshot download succeeds.
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  - `SHA256SUMS` verifies every downloaded file.
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  - No Hugging Face token-looking strings were found.
RELEASE_AUDIT.md CHANGED
@@ -1,6 +1,6 @@
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  # BERTose/AFFINose Training Code Release Audit
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- Date: 2026-05-17
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  ## Current Hugging Face State
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@@ -8,10 +8,10 @@ Fresh no-token readback showed the public inference/model repositories are open.
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  | Repository | Public | Gated | Snapshot | Training code present |
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  |---|---:|---:|---|---:|
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- | `supanthadey1/bertose-glycan-encoder` | yes | no | `c9a7401348ea` | no |
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- | `supanthadey1/bertose-iar-resolver` | yes | no | `5f33f647b403` | no |
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- | `supanthadey1/affinose-interaction-model` | yes | no | `44fcadaa1e4d` | no |
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- | `supanthadey1/bertose-affinose-inference` | yes | no | `9729ebda91a9` | no |
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  | `supanthadey1/bertose-affinose-training-code` | yes | no | see current Hub head | yes |
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  Conclusion: the Hugging Face release is split cleanly between inference artifacts and the dedicated training/reproducibility companion.
@@ -27,7 +27,7 @@ huggingface_release/bertose-affinose-training-code/
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  It contains:
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  ```text
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- 129 files, approximately 54 MB
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  ```
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  The repository is a curated public training/reproducibility companion. It includes code, configs, vocabulary/split metadata, package-local dependencies, and provenance notes. It intentionally does not include the multi-GB corpora, intermediate mappings, checkpoints, generated figures, or full result bundles.
@@ -78,6 +78,7 @@ The following checks passed on the uploaded Hugging Face repository with `token=
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  - `private=False` and `gated=False`.
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  - Required public files are present, including the repaired training modules.
 
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  - Full no-token snapshot download succeeds.
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  - Downloaded snapshot passes `SHA256SUMS` verification and coverage checks.
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  - Downloaded snapshot has no `.secrets`, `__pycache__`, `.pyc`, or `.DS_Store` artifacts.
 
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  # BERTose/AFFINose Training Code Release Audit
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+ Date: 2026-06-10
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  ## Current Hugging Face State
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  | Repository | Public | Gated | Snapshot | Training code present |
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  |---|---:|---:|---|---:|
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+ | `supanthadey1/bertose-glycan-encoder` | yes | no | `62e2bb88557c` | no |
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+ | `supanthadey1/bertose-iar-resolver` | yes | no | `68938794e4af` | no |
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+ | `supanthadey1/affinose-interaction-model` | yes | no | `f13784cb11c7` | no |
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+ | `supanthadey1/bertose-affinose-inference` | yes | no | `8b9eee2aac0c` | no |
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  | `supanthadey1/bertose-affinose-training-code` | yes | no | see current Hub head | yes |
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  Conclusion: the Hugging Face release is split cleanly between inference artifacts and the dedicated training/reproducibility companion.
 
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  It contains:
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  ```text
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+ 130 files, approximately 54 MB
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  ```
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  The repository is a curated public training/reproducibility companion. It includes code, configs, vocabulary/split metadata, package-local dependencies, and provenance notes. It intentionally does not include the multi-GB corpora, intermediate mappings, checkpoints, generated figures, or full result bundles.
 
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  - `private=False` and `gated=False`.
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  - Required public files are present, including the repaired training modules.
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+ - Model card license metadata is `apache-2.0`, and each public repo contains an Apache-2.0 `LICENSE` file.
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  - Full no-token snapshot download succeeds.
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  - Downloaded snapshot passes `SHA256SUMS` verification and coverage checks.
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  - Downloaded snapshot has no `.secrets`, `__pycache__`, `.pyc`, or `.DS_Store` artifacts.
SHA256SUMS CHANGED
@@ -1,8 +1,8 @@
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  a7d0dbe3088ee22e14bd9e1d1ddf56ba4efbb7c8a79ae59e309787ba604e5a09 .gitattributes
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  a6cba85bc92e0cff7a450b1d873c0eaa2e9fc96bf472df0247a26bec77bf3ff9 LICENSE
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- 5ff112e5da352d3f1d7b97853619657d9aa45f2ff56cdd0bea5b37c980bc0353 MANIFEST.md
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  209bf0a55525d3f3d3f3b4e4efe1c110662ac7eac24df94511a146a005b6d730 README.md
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- dca1e3ad57e865047b8e19a26763c675229faeec8ce6a1f9a278ee8d2b23bbec RELEASE_AUDIT.md
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  7286c5016e3b03dda7b49d852bcea37722b3ba9028f3715af35c708bab3e1051 code/affinose/README.md
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  bdeef1f7f1ef86f10e36fb75105d5a298a6d0af76041adab60605430cc6377d0 code/benchmarks/calculate_rankings.py
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  07e21e7ec893453bf60a805abda0f177592d10dbf7af28dd609c763f35c68d4d code/benchmarks/consolidate_results.py
 
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  a7d0dbe3088ee22e14bd9e1d1ddf56ba4efbb7c8a79ae59e309787ba604e5a09 .gitattributes
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  a6cba85bc92e0cff7a450b1d873c0eaa2e9fc96bf472df0247a26bec77bf3ff9 LICENSE
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+ da124040868d09023b0cf8babe348d153300fb1a91db31c625d8873c1a3c0142 MANIFEST.md
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  209bf0a55525d3f3d3f3b4e4efe1c110662ac7eac24df94511a146a005b6d730 README.md
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+ 7c395b48f5234602ff8f5e12adb1e24932d460a05dfa522ba3ae245d15f469a1 RELEASE_AUDIT.md
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  7286c5016e3b03dda7b49d852bcea37722b3ba9028f3715af35c708bab3e1051 code/affinose/README.md
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  bdeef1f7f1ef86f10e36fb75105d5a298a6d0af76041adab60605430cc6377d0 code/benchmarks/calculate_rankings.py
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  07e21e7ec893453bf60a805abda0f177592d10dbf7af28dd609c763f35c68d4d code/benchmarks/consolidate_results.py