MiddleOut Lattice

Lossless compression for model files and tensor archives. It is intentionally model-agnostic: if a model can be represented as files, this can test it.

What this does

• exact round-trip compression for arbitrary bytes
• per-file codec comparison with skip-when-bigger behaviour
• blockwise archive compression with metadata
• a compressed model-store runtime that reads files on demand
• tensor-shard compression with Mosaic and lattice packing
• report generation
• SVG + PNG benchmark chart output
• template data for Qwen2.5-0.5B

Demo and docs

• file 'docs/TECHNICAL_REPORT.md'
• file 'docs/PAPER_OUTLINE.md'
• file 'docs/COMPRESSED_MODEL_STORE.md'
• file 'docs/NEW_ALGORITHM.md'
• file 'data/qwen_template.csv'
• file 'paper/main.tex'
• live demo: https://amsach.github.io/projects/middleout-lattice/demo/
• paper page: https://amsach.github.io/papers/middleout-lattice-paper/

New compression direction

The current architecture now has a blockwise archive layer that can:

• choose the best codec per block
• leave files uncompressed when that is cheaper
• store a manifest with per-file metadata
• decompress the whole tree back exactly

Model-store runtime

CompressedModelStore can keep a model repo compressed at rest and materialise files on demand.

from pathlib import Path
from middleout_lattice import CompressedModelStore

store = CompressedModelStore.from_source(Path("./model_repo"), Path("./packed"))
print(store.summary())
print(store.read_bytes("config.json")[:80])

New algorithm

• Mosaic Archive Packing: a reversible entropy-aware byte-plane transform plus residual coding, now with lattice fallback.
• Details: file 'docs/NEW_ALGORITHM.md'

Tensor-shard codec

• tensor_shards.py compresses safetensors-like blobs per tensor.
• It now compares raw, generic, Mosaic, and lattice encodings.

What this does not promise

• It does not invent a universal free lunch.
• It does not pretend every checkpoint will hit 2x lossless.
• It does keep the decode exact.

Paper PDF

• file 'build/main.pdf'