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test

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Cannot load the dataset split (in streaming mode) to extract the first rows.

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
prefix: list<item: string>
  child 0, item: string
region_old: list<item: string>
  child 0, item: string
region_new: list<item: string>
  child 0, item: string
model_target: string
note: string
parent_kind: string
k_partial: int64
partial_lines: list<item: string>
  child 0, item: string
psm_prompt: string
psm_target: string
family: string
package: string
path: string
cursor_idx: int64
event_diff: string
suffix: list<item: string>
  child 0, item: string
corpus_target: string
case: string
case_version: int64
template_index: int64
backend: string
model: string
full_prompt: string
generated_at: timestamp[s]
seed: int64
corpus_key: string
content_hash: string
license: string
source_url: string
generator: string
key: string
ok: bool
ts: timestamp[s]
hash: string
to
{'key': Value('string'), 'ok': Value('bool'), 'hash': Value('string'), 'ts': Value('timestamp[s]')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              prefix: list<item: string>
                child 0, item: string
              region_old: list<item: string>
                child 0, item: string
              region_new: list<item: string>
                child 0, item: string
              model_target: string
              note: string
              parent_kind: string
              k_partial: int64
              partial_lines: list<item: string>
                child 0, item: string
              psm_prompt: string
              psm_target: string
              family: string
              package: string
              path: string
              cursor_idx: int64
              event_diff: string
              suffix: list<item: string>
                child 0, item: string
              corpus_target: string
              case: string
              case_version: int64
              template_index: int64
              backend: string
              model: string
              full_prompt: string
              generated_at: timestamp[s]
              seed: int64
              corpus_key: string
              content_hash: string
              license: string
              source_url: string
              generator: string
              key: string
              ok: bool
              ts: timestamp[s]
              hash: string
              to
              {'key': Value('string'), 'ok': Value('bool'), 'hash': Value('string'), 'ts': Value('timestamp[s]')}
              because column names don't match

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Check out the documentation for more information.

Sepalith dataset

Open, R-specialized next-edit-suggestion training data. Private.

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

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 fetch stats.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).

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Total file size:

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Sepalith dataset

Layout (read this first)

The pretraining package (pretraining/)

Corpus licensing (the standing rule)

Source labels in families/

The pretraining package (`pretraining/`)