Datasets:

Arain119
/

Sophia-dataset

Tasks:

Text Generation

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xet

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train

The dataset viewer is not available for this split.

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

Error code:   StreamingRowsError
Exception:    ValueError
Message:      Expected object or value
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 342, in pyarrow._json.read_json
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
                  raise convert_status(status)
              pyarrow.lib.ArrowInvalid: JSON parse error: Column() changed from object to string in row 0
              
              During handling of the above exception, another exception occurred:
              
              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 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

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Sophia 训练数据集

Sophia 1B 模型的全部训练数据资产，两部分：

`pretrain/` — 预训练 token 分片（约 80 GB）

用于 Sophia 随机初始化预训练和兼容 checkpoint 的继续预训练。不是文本 benchmark，也不是 SFT 数据集。

pretrain/
  dataset_manifest.json      # 根 manifest：绑定三个 split、tokenizer bundle、lineage，
                             # 以及每个 shard 的 token count、bytes、SHA-256
  train/   manifest.json + shard_*.bin（875 shards）
  val/     manifest.json + shard_*.bin（1009 shards）
  test/    manifest.json + shard_*.bin（1012 shards）
  lineage/                   # 来源清单、清洗报告、配比策略、基准签名

token dtype 为 int32。修改 tokenizer、manifest 或任意 shard 后，原 admission 证据失效。

使用：

export SOPHIA_DATA_PATH=/path/to/pretrain

训练前验证：

python3 - <<'PY'
from ml.training.pretrain.data_admission import validate_pretrain_dataset_manifest

validate_pretrain_dataset_manifest(
    data_path="/path/to/pretrain",
    tokenizer_path="ml/modeling/text",
)
print("production_dataset_admission=pass")
PY

正式训练只读取一个 train split；没有 decay-data 或运行中动态 mix。不要拆分、重排、手改 manifest 或混用来自另一 tokenizer 的 shards。

`corpus/` — SFT 监督微调语料（约 426 MB）

依赖脚本蒸馏 + 机器判官筛选的对话语料：train.jsonl 88,267 行、val.jsonl 1,500 行、profile.json 数据集画像。详见 corpus/README.md。

权利与许可证

corpus/：Apache License 2.0
pretrain/：由具有各自来源条款的语料构成，部分上游来源仅限研究/非商用用途。根 manifest 和 pretrain/lineage/ 是使用合同的一部分；本仓库许可证字段不能替代上游许可证、平台条款或内容权利。使用者必须按 lineage 核对用途和再分发范围。

Sophia 训练数据集

pretrain/ — 预训练 token 分片（约 80 GB）

corpus/ — SFT 监督微调语料（约 426 MB）

权利与许可证

相关仓库

`pretrain/` — 预训练 token 分片（约 80 GB）

`corpus/` — SFT 监督微调语料（约 426 MB）