Fabryka.AI

FABRYKA AI / RESEARCH NOTES

Keep the evidence.
Build on the work.

Research reports, reproducible experiments and technical notes from our public repositories, followed by the earlier archive.

OPEN RESEARCH / ACROSS THE REPOSITORIES

More questions.
More evidence.

Nine selected notes across six public repositories: small models, Polish tokenizers, evaluation and data preparation. Browse measured results, provisional pilots and technical methods with their source records.

RESEARCH ATLAS / FOLLOW THE CONNECTIONS

What builds on what?

From data and representation to measurement and decisions. Select a note to see the connection, its purpose and the source evidence.

Documented reuseConceptual connectionArrows show relationships, not a timeline.
Research relationships: data, measurement and decisionsSix selectable research notes. Solid arrows show documented reuse: Probierz to Fabryka Track, and the Polish agreement probe to benchmark cost planning. Dashed arrows connect research questions without asserting implementation lineage. All connections are described below.PREPARE & REPRESENTDEFINE & PROBERECORD & DECIDEDifferent token counts → a common unitAudit overlap before interpreting scoresScoring tools + syntax itemsMeasured runtime + observed contrastFrom a score to a useful decision01 / REPRESENTATIONPolish BPEImplementation & pretokenisation371-word held-out ↗02 / DATA QUALITYDataset cleaningPipeline gaps & experimentsProposals to test ↗03 / MEASUREMENTProbierzWhat should a benchmark measure?Method + runnable tools ↗04 / PILOTPolish agreement probeKoliber × Pollock2,000 pairs · provisional ↗05 / RECORDED EVIDENCEFabryka Track panelCompression + Polish syntax5 models · historical panel ↗06 / NEXT DECISIONBenchmark costHow much useful signal per run?Measured pilot + cost proxies ↗Why measure this again?

Scroll the diagram sideways, or select a note below.

01 / REPRESENTATION

Polish BPE

A handwritten byte-level BPE is compared with Hugging Face variants at the same 6,756-token vocabulary. The question is how implementation and pretokenisation change compression.

The reported range is 833–844 tokens on a small held-out. It does not establish a downstream model-quality gain.

Read this research note ↗

What connects it — and why

  • Conceptual connection

    Polish BPE → Probierz

    Different token counts → a common unit

    The BPE experiment shows that token counts depend on tokenisation. This motivates looking beyond per-token quantities when comparing models. The recorded panel uses bits per byte; this is a methodological connection, not evidence that Probierz used this tokenizer.

02 / DATA QUALITY

Dataset cleaning

The audit compares the existing data pipeline with published corpus-cleaning approaches and identifies candidate quality, deduplication and filtering checks.

This is a gap analysis for future experiments, not a measured cleaning ablation.

Read this research note ↗

What connects it — and why

  • Conceptual connection

    Dataset cleaning → Polish agreement probe

    Audit overlap before interpreting scores

    Data-cleaning research includes evaluation-overlap checks. The Ladder pilot explicitly leaves training-overlap review pending. Both address the same validity problem; no shared implementation is established by these notes.

03 / MEASUREMENT

Probierz

Probierz defines measurement dimensions, provenance and overlap checks, and a programme of falsifiable evaluation. It also provides scoring tools used by the recorded model panel.

The panel is evidence for particular metrics, not validation of the entire multidimensional measurement programme.

Read this research note ↗

What connects it — and why

  • Conceptual connection

    Polish BPE → Probierz

    Different token counts → a common unit

    The BPE experiment shows that token counts depend on tokenisation. This motivates looking beyond per-token quantities when comparing models. The recorded panel uses bits per byte; this is a methodological connection, not evidence that Probierz used this tokenizer.

  • Documented reuse

    Probierz → Fabryka Track panel

    Scoring tools + syntax items

    The Track result manifest identifies Probierz’s scorer_hf.py, bpb_scorer.py, run_forced_choice.py and d3 syntax eval items, including hashes. These tools and items turn part of the measurement programme into a recorded model panel.

04 / PILOT

Polish agreement probe

A matched-item pilot records continuous pair probabilities and runtime for Koliber and Pollock. Its measurements supply the cost-planning note.

Native review and overlap checks are pending. Corpus BPB and training-seed variance were not measured; language-training domains differ.

Read this research note ↗

What connects it — and why

  • Conceptual connection

    Dataset cleaning → Polish agreement probe

    Audit overlap before interpreting scores

    Data-cleaning research includes evaluation-overlap checks. The Ladder pilot explicitly leaves training-overlap review pending. Both address the same validity problem; no shared implementation is established by these notes.

  • Documented reuse

    Polish agreement probe → Benchmark cost

    Measured runtime + observed contrast

    The cost note explicitly reuses the 2,000-pair pilot: 111.3 seconds for Koliber, 100.4 seconds for Pollock and an observed probability difference of 0.3169. It uses these measurements to anchor workload estimates; it cannot compute seed-calibrated DF.

05 / RECORDED EVIDENCE

Fabryka Track panel

The result archive stores per-document compression scores, paired-bootstrap artifacts and a syntax panel. Its manifest names and hashes Probierz scoring tools and syntax items.

BPB uses 300 documents; the reported syntax core contains 148 pairs. This panel and the Ladder pilot use different items and metrics.

Read this research note ↗

What connects it — and why

  • Documented reuse

    Probierz → Fabryka Track panel

    Scoring tools + syntax items

    The Track result manifest identifies Probierz’s scorer_hf.py, bpb_scorer.py, run_forced_choice.py and d3 syntax eval items, including hashes. These tools and items turn part of the measurement programme into a recorded model panel.

  • Conceptual connection

    Fabryka Track panel → Benchmark cost

    From a score to a useful decision

    The historical panel reports scores and uncertainty. Ladder asks the additional question: can a metric distinguish the intended models reliably enough to justify its cost? This connects research questions; the cost note does not claim to reuse the Track panel.

06 / NEXT DECISION

Benchmark cost

The planning note reuses the Polish pilot’s observed runtimes and contrast, then estimates the workload of other benchmarks to plan the next paired evaluation.

English-battery times are proxies. Seed-calibrated discrimination is unavailable, so the note does not establish which benchmark should be adopted.

Read this research note ↗

What connects it — and why

  • Documented reuse

    Polish agreement probe → Benchmark cost

    Measured runtime + observed contrast

    The cost note explicitly reuses the 2,000-pair pilot: 111.3 seconds for Koliber, 100.4 seconds for Pollock and an observed probability difference of 0.3169. It uses these measurements to anchor workload estimates; it cannot compute seed-calibrated DF.

  • Conceptual connection

    Fabryka Track panel → Benchmark cost

    From a score to a useful decision

    The historical panel reports scores and uncertainty. Ladder asks the additional question: can a metric distinguish the intended models reliably enough to justify its cost? This connects research questions; the cost note does not claim to reuse the Track panel.

Two reuse links are documented in the inspected notes. Three dashed links are editorial interpretations of shared research questions. They do not imply a shared codebase, dataset or chronological dependency. Sources are pinned to the revisions used in this catalogue.

Workshop research · tokenizer

Polish BPE: implementation and pretokenisation

Small held-out · 371 words

Evaluation planning note · ladder

Benchmark cost versus discrimination

Measured probe + explicit cost proxies

These are selected research notes and artifacts, not nine peer-reviewed papers. Measurements retain their own datasets and protocols; scores from different studies are not combined.

Experiments & engineering

Log eksperymentów

Experiment log · source last updated 15 June 2026. Training recipes, tokenizer measurements, failures and limitations.

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V4 Faza 0: regresja CDSC-E była głównie artefaktem pomiaru, a kalibracja λ to pułapka małej próbki

14 June 2026 · Measurement and calibration investigation.

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Slayer v3 poprawił LLMzSzŁ, ale uderzył w CDSC-E. To jest czerwona flaga

13 June 2026 · A documented model regression and its evaluation context.

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Munin 1.0 nie zrobił CPT. Receptura wyciekła w nazwie katalogu

13 June 2026 · Training-recipe investigation and lessons learned.

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Data & methodology

Models and datasets

Historical catalogue dated 4 September 2026. Follow the original repository links for current versions and licences.

Browse the archive →

How we measure

Research questions, matched comparisons, data provenance and inspectable artifacts.

Read our methodology →