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LOG/EXP units verified bit-exact over all 65,536 (a,b) pairs,
the same N/N discipline as
neural-aarch64-units.Honest by design: dedup removes redundant data; RS adds redundancy for resilience. Incompressible data never shrinks — you cannot beat entropy. Chunk hashes are real SHA-256, not a neural emulation.
GF256 (LOG/EXP): GF(2⁸) multiply — composed multiply 65536/65536Vault: dedup + RS shards on disk, survives deleted/corrupted shards, heal()sVaultFS + optional WinFsp drive-letter mount1pip install torch
2python step1_storage.py # verified GF(256) + dedup chunk store
3python step2_rs.py # Reed-Solomon recovery
4python step3_vault.py # self-healing vault
5
6python cli.py store <vault> <folder>
7python cli.py export <vault> <folder> # RS-healed reconstruct
8python cli.py mount <vault> X: # requires WinFsp
9
10# image a whole drive/partition into a self-healing .pt (may need admin):
11python cli.py image \\.\C: diskC.pt
12python cli.py image-verify diskC.pt
13python cli.py image-restore diskC.pt out.imgGF256.pt.storage/gf256.py): write the exact
golden finite function → enumerate the domain (decompose big/linear ones into
bit/byte slices, see storage/rs.py) → common.train → common.verify must be
bit-exact on 100% of inputs → compose. step1_storage.py shows the full loop.1@misc{byrne2026neuralstorage,
2 title = {neural-storage: Self-Healing Erasure-Coded Vault with a Verified GF(256) Core},
3 author = {Byrne, Dean (Quazim0t0)},
4 year = {2026},
5 howpublished = {\url{https://huggingface.co/NeuralVerified/neural-storage}}
6}Now hosted by NeuralVerified.This repo was moved into the NeuralVerified organization to help organize my profile. Originally published atQuazim0t0/neural-storage.