Artifact contract

A readable ~0.8M-parameter transformer whose byte tokenizer, architecture, loss, and checkpoint format are all inspectable.

This model checkpoint is classified as runnable lab. Workload guidance: light first; training duration is user-controlled.

Build

Train the tiny preset on the bundled corpus.

Modify

Change layers, heads, width, or context in the source-of-truth model config.

Tune

Change learning rate, batch size, seed, or step budget one variable at a time.

Prove

Inspect initial loss, tiny-overfit behavior, samples, and tensor inventory.

Package

Keep a validated .tinygpt checkpoint with its exact config and corpus.

CLI surface

Run: posttrainllm train
Run: posttrainllm inspect
Run: posttrainllm validate

How to read this dossier

This canonical page separates the retained repository decision from the material that informed it. A source may describe an external claim, historical measurement, local observation, or planned procedure; those evidence classes are not interchangeable. Follow the provenance links before reusing a number or method.

Status and disposition describe what PostTrainLLM retained when this record was indexed. They are not a live product promise, a newly run benchmark, or permission to restart historical work. Unknown or unmeasured fields remain unknown rather than being treated as zero.

To reuse the record, first name the exact claim you need and trace it to the linked source. Then check whether the original environment, model revision, data split, evaluator, hardware, and budget match the proposed use. If they do not, treat the record as a hypothesis or design reference and run the smallest fresh comparison that can falsify it. Preserve negative outcomes and regressions beside any improvement; a local win on one slice does not silently become a general capability claim.

Source provenance

The normalized record comes from docs/learn/artifact-journey.json. The links below are the tracked evidence and explanatory sources preserved with the record.

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