posttrainllm docs
Mac-local LLM specialist factory — training, inference, evals, systems notes, and learning paths.
posttrainllm documentation
posttrainllm is a Mac-local specialist factory: target → data → post-training → eval → package → report. These docs are the committed source of truth; this site is the presentation + search layer over them.
Prefer the markdown mirrors (append .md to any URL) and llms.txt for
agents. The full corpus is also at /llms-full.txt after build.
Start here
- How it works — learning-first end-to-end walkthrough of the factory loop, runtime, and design decisions
- Project status — current state, active scope, shipped vs parked surfaces
- Active queue — what to do next and what not to touch
- Factory contract — run schema, eval protocol, packaging, reports
- Capability matrix — what the factory CLI actually does
- Learn path — ground-up curriculum and concept references
- Data inventory — datasets and provenance
- Frontier-parity result — the strongest measured claim
Navigation
| Surface | Use it for |
|---|---|
/factory |
Run schema, eval protocol, packaging, public artifacts, enforcement |
/techniques |
Method-vs-recipe registry and target-specific technique backlogs |
/attempt-ledger |
What worked, failed, regressed, or remains untried |
/external-products-reviewed |
Products, papers, startups reviewed and what we stole or rejected |
/recipes |
Closed-loop recipes (traces → SFT → specialist, distillation, eval-gate) |
/parked |
Paused lanes and why they are paused |
/doc-status |
Status label (active/evidence/reference/learning/parked/superseded/archive) for every major doc |
For the maintainer golden path through the docs (the order a new reader should
read them in), see README.md. When docs disagree, the conflict
rule lives in doc-status.md.