ProCreations/minima-spellcheck

Minima Spellcheck

A strict packed W1.58A8 adaptation of LiquidAI/LFM2.5-Encoder-350M-Spellchecker, built with SSHDotCodes/minima.

• Logical matrix values: {-1, 0, +1} (1.585 bits)
• Physical artifact format: I2_S, four trits per byte
• Group size 128, no recovery adapters
• Full encoder context: 8,192 tokens
• Packed weight file: 90.7 MB (95,128,472 bytes)
• CPU demo: Minima Spellcheck

Use

pip install "minima-lfm @ git+https://github.com/SSHDotCodes/minima.git"

from minima import MinimaModel

model = MinimaModel.from_pretrained("ProCreations/minima-spellcheck", device="cpu")
print(model.correct(
    ["I has went to the stor yesterday ."],
    max_iter=4,
    min_error_prob=0.0,
    rerank=False,
))

Validation

Teacher-agreement diagnostics against the LiquidAI tagger with the optional dense reranker disabled on both sides:

Diagnostic	Result
Tag top-1 agreement within teacher candidates	99.44%
Error-detection top-1 agreement	99.49%
Exact correction agreement, held-out + reference examples	38.2% (68 texts)
Exact agreement on the published-style examples	25%

Input	Minima
She go to school every day .	She go to school every day .
I has went to the stor yesterday .	I has went to the store yesterday .
Their are many reason to study hard .	Their are many reasons to study hard .
That 's a fair point , let 's discuss it tomorrow .	That 's a fair point , let 's discuss it tomorrow .

The upstream optional reranker is disabled because it contains a separate 1.42 GB dense encoder, which would invalidate this model's CPU memory profile.

License

The weights remain subject to the LFM Open License v1.0 shipped in this repository. The Minima runtime code is MIT licensed.