File size: 2,861 Bytes
bdfb884 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 | ---
license: mit
library_name: pytorch
tags:
- verified-units
- reed-solomon
- erasure-coding
- deduplication
- storage
---
# neural-storage — self-healing vault with a verified GF(256) core
**Repositories:** [GitHub](https://github.com/quzi93/neural-storage) · [🤗 HuggingFace](https://huggingface.co/NeuralVerified/neural-storage)
A content-addressed, deduplicating, **self-healing** storage vault. Any *k* of *n*
Reed-Solomon shards reconstruct the whole, so pieces can be lost or corrupted and
the data survives. The erasure-coding arithmetic — GF(2⁸) multiply — is provided
by neural `LOG`/`EXP` units verified **bit-exact over all 65,536 (a,b) pairs**,
the same N/N discipline as
[neural-aarch64-units](https://huggingface.co/NeuralVerified/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.
## What's verified
- `GF256` (`LOG`/`EXP`): GF(2⁸) multiply — **composed multiply 65536/65536**
- Reed-Solomon any-*k*-of-*n* recovery (every loss pattern)
- `Vault`: dedup + RS shards on disk, survives deleted/corrupted shards, `heal()`s
- `VaultFS` + optional WinFsp drive-letter mount
## Use
```bash
pip install torch
python step1_storage.py # verified GF(256) + dedup chunk store
python step2_rs.py # Reed-Solomon recovery
python step3_vault.py # self-healing vault
python cli.py store <vault> <folder>
python cli.py export <vault> <folder> # RS-healed reconstruct
python cli.py mount <vault> X: # requires WinFsp
# image a whole drive/partition into a self-healing .pt (may need admin):
python cli.py image \\.\C: diskC.pt
python cli.py image-verify diskC.pt
python cli.py image-restore diskC.pt out.img
```
Weights: `GF256.pt`.
**Create your own verified unit** (template: `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.
## Citation
```bibtex
@misc{byrne2026neuralstorage,
title = {neural-storage: Self-Healing Erasure-Coded Vault with a Verified GF(256) Core},
author = {Byrne, Dean (Quazim0t0)},
year = {2026},
howpublished = {\url{https://huggingface.co/NeuralVerified/neural-storage}}
}
```
**Dean Byrne (Quazim0t0)** · 2026
---
<!-- neuralverified-relocation-note -->
> **Now hosted by [NeuralVerified](https://huggingface.co/NeuralVerified).**
>
> This repo was moved into the NeuralVerified organization to help organize my profile.
> Originally published at [`Quazim0t0/neural-storage`](https://huggingface.co/Quazim0t0/neural-storage).
|