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schema int64 | document_id string | package string | group_id string | cpt_partition string | source_path string | source_sha256 string | row_id string | chunk_index int64 | input_ids list | labels list | attention_mask list | source_token_start int64 | source_token_end int64 | token_start int64 | token_end int64 | document_token_count int64 | overlap_context_tokens int64 | is_document_end bool | supervised_tokens int64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
Sepalith dataset
Open, R-specialized next-edit-suggestion training data. Public.
Layout (read this first)
The repo is a projection of the working corpus (a NAS). Everything here is either (a) source data with its license trail, (b) derived synthetic families, or (c) assembled training mixtures. Heavy raw corpora are summarized at ledger/manifest level here; full content lives on the source system (see each corpus entry below).
| path | what it is |
|---|---|
pretraining/ |
The A2 training package (2026-08-26): token-id block files (int32, 1025×N overlap-1), the 32K tokenizer, the mixture manifest, repack stats + contamination gate — everything run.py all needs on a rented instance (see below) |
corpus/cran/ |
The era-1 CRAN corpus: full package shards (packages/), licenses.jsonl, manifest.jsonl |
corpus/bioc/ |
Bioconductor corpus: license ledger + manifest (content level: ~0.35-0.55B tokens on source) |
corpus/stack_v2/ |
StackOverflow-R corpus: license ledger, measure + dedup reports (1.645B net-new tokens measured) |
corpus/stack_v3/ |
GitHub-R tranche: acceptance report (contamination-corrected; 143.5M net-new) |
corpus/pwc/ |
Papers-with-code R tranche: license ledger, manifest, measure report (~40M tokens) |
families/<family>/<source>.jsonl |
Synthetic case families — one file per author source. Rows carry base_sample_id (content-hash parent link) + rule/backend tags |
mixtures/sft_vX/ |
Assembled train/eval splits (derived; rebuilt from families by experiments/post-processing/assemble_sft_v5.py) |
provenance/ |
Per-package provenance records |
datasets/ |
Package index + top-level manifest |
campaign-20260915/ |
The September 2026 full-weight campaign: editing-SFT TRAIN rows, roxygen queue, draw schedules, DEV75 panel, CPT cohort, and a provenance archive (see below) |
The pretraining package (pretraining/)
Layout mirrors the training data-root exactly, so the whole package is consumable in two commands from a fresh instance:
hf download scholzmx/sepalith --repo-type dataset \
--include "pretraining/*" --local-dir /data
python3 run.py all --data-root /data # verify→repack(skip)→manifest→train→gates
a2_transfers/<stratum>/blocks.npy— transfer strata (english, python_v2, c_cpp, js_ts, sql, julia, matlab, curated python), each with its fetchstats.json(SWH-origin stack-v2 content, permissive-only, sha1-verified)a2/r/*.npy— the R strata:r_causal(CRAN plain-doc render),r_fim_mix(PSM + random-cursor + no_op, the validated mix),r_noop,so_r_qa(the Stack v3 R keep set: answer-CODE, ODC-By-1.0, deduped — NOT Q&A prose),bioc(Bioconductor current R/tests; man/ excluded per the roxygen double-count rule), plus held-out eval slices with byte counts (BPB denominators)a2/r/stats.json+a2/r/contamination.json— repack accounting and the contamination gate verdict (git-mirror = hard-fail gate, internal eval slices = package-disjoint by construction, warn-only)datasets/a2_tokenizer_v1/tokenizer.json— the frozen 32K tokenizer (eos<|endoftext|>id 5)a2_mixture_manifest.json— per-stratum block paths, draw shares, token counts, epochs-equivalent (repetition is surfaced, never silent; so_r_qa/bioc shares are provisional pending the GO-time re-cut)
Deferred R sources (documented, not in the package): full-CRAN causal
beyond astfim's span sample, git/ GitHub-R repos (license audit
pending), CRAN Archive (edit-diff), vignettes/prose slice, and the
English×R Q&A-prose bridge. Eval-protected assets (the transfer org
mirror, R eval holdouts) never enter training data.
Corpus licensing (the standing rule)
Permissive only (MIT/Apache/BSD/GPL-family/CC-BY/CC0; NC/ND excluded and ledgered). Every corpus directory carries its license ledger or report; exclusions are recorded, not silently dropped.
Source labels in families/
glm-5.3 (zai), gemini-3.7-flash (agy), muse-spark-1.2 (opencode GO/free), x-preview (zen), model-id (openrouter), corpus = deterministic/mined (no LLM authorship).
The September 2026 campaign (campaign-20260915/)
Data for the full-weight continued pretraining and editing SFT of the Sepalith 2B model. The weights are in scholzmx/sepalith-2b-cpt.
| Path | What it is |
|---|---|
sft/DAT10-finish-source-repair-v3/ |
15,006 pre-tokenized editing-SFT TRAIN rows (train-token-rows.jsonl), their context sidecar, the repair ledger and materialization receipts |
sft/roxygen-supported-context-v1/ |
10,017 roxygen-drafting candidates with selected context. Reviewed but not admitted to training |
sft/schedules/ |
Prepared draw schedules for the 15,006-row cohort |
dev/corrected-dev75-v1/ |
The 75-case development panel (43 edit, 32 no-op) and its manifest |
cpt/CPT-prefix-extension-v1/ |
The CPT cohort rows (16K context, 471.9M input tokens, 10,046 packages), the cohort manifest and the final draw schedule |
cpt/validation/ |
The 499-case 2K held-out CPT validation panel |
provenance/ |
Campaign receipts, packet manifests and code as a tarball, plus its file list. It contains no row-level data |
TRAIN, DEV and the sealed final evaluation set are split-disjoint by identity group. The sealed final set is intentionally absent from this repository.
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