Swordnael/LFM2.5-Fable-Router-Curriculum

Autonoma Fable router curriculum — reproducibility package

This public repository documents and reproduces the router-only curriculum for an experimental LFM2.5-2.6B Fable hybrid. It intentionally does not redistribute records derived from a source whose license is unknown.

Included

• fable-router-curriculum.v2.json: immutable training/data policy.
• build_fable_router_curriculum.py: deterministic local builder.
• REPRODUCIBILITY_MANIFEST.json: pinned sources, input/output hashes, row counts, exclusions, and build command.
• training/: the non-routing router shell, pure provenance validators, and free-GPU structural-smoke runner.
• fable-router-cloud-smoke.v1.json: immutable host, bank, curriculum, hash, hardware, and evidence gates for that runner.

Given independently authorized access to the two public sources, these files reproduce the exact materialized artifacts by SHA-256. They also expose the split, deduplication, overflow, anti-loop, duplicate-tool, benefit-gated routing, and anti-collapse decisions for review.

Materialized result

The internally verified build produced:

File	Rows	SHA-256
sft-train.jsonl	6,084	10a72911887aa642339b78c11ed12f3540ada2076a81dc13fc99566bf522bd13
sft-validation.jsonl	341	b2925d1699a83ea48649905a6e922e311f34e355bdbf22b0b573692358643e66
sft-test.jsonl	330	7ddd0e5865ba54c12d1aca9ca8b87fa078742d2a115ab56137125757ac343421
preference-train.jsonl	4,099	9924541e4a5b40710e14a370119d7571e71bb2f881433b6bd5807cc1c76dc8a4

The split unit is normalized prompt hash for reasoning data and immutable source trajectory SHA-256 for agent/coding data. No identity crosses a split. Frozen evaluation prompts and answers are excluded from the builder.

Source policy

• greghavens/fable-5-coding-and-debugging-traces at c63e82adec30798edcbd6e1dcb0014d2b15de236 declares CC-BY-4.0.
• HelioAI/Claude-Fable-5-5500x at 440267fbdb1b00a40216e7233dbce25530a0ed09 declares license: unknown and explicitly tells users to verify compliance before redistribution or derivative training.

Public availability is not itself a redistribution license. Accordingly, this public package contains references and reproducibility code, not copied Fable reasoning records. The materialized artifacts remain in a private companion repository pending a compatible license or a rebuild without that source.

Reproduction

Place the pinned source files at the paths declared in the builder, provide the pinned Fable tokenizer, then run:

python scripts/bench/build_fable_router_curriculum.py

The builder rejects malformed or overlong examples, deduplicates reasoning prompts, samples cumulative agent prefixes by immutable trajectory, creates train-only anti-loop preference pairs, and writes a provenance-bound result.json. Final training must retokenize with the actual chat template and reject overflow above 2,048 tokens rather than truncate it.

Publication of this package does not authorize training, routing, deployment, or promotion in Autonoma.

Structural smoke boundary

The structural smoke validates every one of a bank's 2,880 tensor records, then materializes only layer 29's 32 experts around the real frozen Fable host. It checks exact host-disabled identity, strict trainable-parameter isolation, nonzero router/scale gradients, explicit host-only and positive-benefit counterfactual targets, router checkpoint parity, and persisted resource telemetry. This is intentionally small enough for a free 16 GiB Colab/Kaggle GPU.

Passing it proves that a donor bank is mechanically trainable. It does not prove full-30-layer memory fit, final quality, throughput, or promotion fitness, and it cannot authorize a training campaign. Every run is uploaded to a private evidence dataset so an ephemeral notebook cannot turn an incomplete or failed result into a pass.