The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 290, in _generate_tables
pa_table = paj.read_json(
io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
)
File "pyarrow/_json.pyx", line 364, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
return check_status(status)
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
raise convert_status(status)
pyarrow.lib.ArrowInvalid: JSON parse error: Column(/sources/[]/license) changed from string to array in row 0
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 101, in _split_generators
pa_table = next(iter(self._generate_tables(**splits[0].gen_kwargs, allow_full_read=False)))[1]
~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 304, in _generate_tables
batch = json_encode_fields_in_json_lines(original_batch, json_field_paths)
File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 111, in json_encode_fields_in_json_lines
examples = [ujson_loads(line) for line in original_batch.splitlines()]
~~~~~~~~~~~^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 20, in ujson_loads
return pd.io.json.ujson_loads(*args, **kwargs)
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
ValueError: Expected object or value
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 68, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
YAT training data: provenance and versions
This public catalog records the distinct prepared corpora used or considered in FlaxChat YAT training. This release contains metadata and references only. It does not yet contain raw training examples or token arrays. The inventory is incomplete where historical artifacts have not been recovered.
Read catalog.json for status, upstream revisions, prepared sizes, metadata SHA-256 values, artifact references, and known gaps. metadata/ holds the original recipe and manifest bytes. A historical_trained or active status is separate from candidate, development, and validation status. Prepared pool size is not training exposure. Recoveries reuse the same frozen corpus rather than defining new data versions.
Versioning
The immutable release tag is catalog-2026-10-10; consumers should pin its resolved Hugging Face commit. Each prepared dataset has a distinct ID and original content/recipe hashes. Corrections receive a new release tag; upstream revisions, splits, tokenizer identity, and sampling seeds must stay explicit. Future 10B preparation receives a separate version, with actual counts published only after completion.
Included families
- FineWeb2-HQ adaptation and pilot selections.
- Historical web/reference MLM mixtures (102M, 359M and 617M prepared nonpadding tokens).
- The current 1.043B multilingual/code MLM pool from October 6, reused by scratch GOAT-input training.
- Global Voices pilot, 28-language continuation, and larger carry-preserving continuation; the unused larger noncarry candidate is separate.
- MS MARCO, MIRACL and CodeSearchNet source references for the released embedding-v1 fine-tune.
- Representation-v2 development/repair references, explicitly incomplete.
Attribution and content licenses
Original sources remain credited in each recipe and upstream revision. FineWeb2-HQ, FineWeb2 and FineWeb-Edu declare ODC-BY dataset licensing; Common Crawl and underlying content terms still apply. Global Voices content is CC-BY-3.0: credit Global Voices contributors, OPUS alignment and Sentence Transformers packaging. The upstream package does not retain article URLs. GitHub code has per-file/repository licenses; a packaging license must not be treated as a blanket license for every code file. MS MARCO, MIRACL, CodeSearchNet and historical reference data require their own applicable source terms. No blanket license is asserted for this mixed catalog.
Only metadata is published here. Releasing content or token arrays requires preserving the corresponding provenance, attribution, and applicable notices; tokenization does not remove content obligations. GCS references document artifact identity and do not imply public access.
Quality limitations
The current 1B recipe performed normalized exact-document deduplication. It does not establish semantic or benchmark-wide decontamination. Historical corpora have different overlap policies recorded in their manifests. All counts and quality claims must be tied to the exact stage and revision; this catalog is not evidence of production quality or complete language/domain coverage.
Training implementation: FlaxChat. Model family: mlnomad on Hugging Face.
- Downloads last month
- -