The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: TypeError
Message: Couldn't cast array of type
struct<trajectories: int64, documents: int64, rounds: struct<4: int64, 3: int64, 5: int64>, ratio_bins: struct<5: int64, 7: int64, 6: int64, 8: int64, 4: int64, 3: int64>, segment_min: int64, segment_max: int64, source_tokens: int64>
to
{'candidates': Value('int64'), 'retained': Value('int64'), 'rejected': {'continuation_length': Value('int64')}}
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 2312, in cast_table_to_schema
cast_array_to_feature(
~~~~~~~~~~~~~~~~~~~~~^
table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
feature,
^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1861, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
~~~~^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2068, in cast_array_to_feature
_c(array.field(name) if name in array_fields else null_array, subfeature)
~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1863, in wrapper
return func(array, *args, **kwargs)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2158, in cast_array_to_feature
raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}")
TypeError: Couldn't cast array of type
struct<trajectories: int64, documents: int64, rounds: struct<4: int64, 3: int64, 5: int64>, ratio_bins: struct<5: int64, 7: int64, 6: int64, 8: int64, 4: int64, 3: int64>, segment_min: int64, segment_max: int64, source_tokens: int64>
to
{'candidates': Value('int64'), 'retained': Value('int64'), 'rejected': {'continuation_length': Value('int64')}}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.
Latent Working Memory 项目数据
本仓库保存 latent_working_memory 项目的数据索引与实验产物。目录以项目根目录为基准，保留原有的 data/ 与 artifacts/ 相对布局；三个 v2 实验系列虽然原先分散存放在服务器的不同磁盘，在这里统一位于 artifacts/v2/。
| 路径 | 内容 |
|---|---|
data/fineweb-reconstruction-k512-doc100k_20260917/ |
共用重构数据索引：preparation.json 及 single/、multi/ 中的 train、dev、test JSONL |
artifacts/v2/reconstruction_20260917/ |
pooling warm-up / dynamic 的四组实验 |
artifacts/v2/reconstruction-independent-prefix_20260921/ |
pooling static 的两组实验 |
artifacts/v2/compressor-structure_20260923/ |
weighted / spectral 的四组实验及结构验证产物 |
每个系列沿用原有的 plan/、train/<run>/、compare/ 等目录；run 内的 checkpoints/*.pt 是原生 PyTorch 训练状态，包含可训练参数、optimizer、训练游标和 RNG，不是可以直接用 transformers.from_pretrained() 加载的完整基座模型。run.json、provenance.json、日志和 SwanLab 本地记录保留原始运行信息。2026-09-27 对 dev/、test.json 和两份 compare/*/analysis.json 的评估字段进行了一次纯 JSON 迁移，没有重新运行模型：递归压缩指标统一位于 multi_compression/*，各位置独立单次压缩指标位于 single_compression/*；最终位置的多次压缩 NLL、单次压缩 NLL 与二者差值分别使用 final_round_multi_compression_{ae,lm}、final_round_single_compression_{ae,lm}、final_round_compression_gap_{ae,lm}。训练配置中的 independent_prefix 仍表示原训练协议。最早的四组（reconstruction_20260917）只记录了最终位置的单次压缩结果，没有各位置单次压缩轨迹；迁移保留该真实结果，但不能补出缺失的逐位置指标。后六组 test 删除了可由逐位置记录重算的最终位置重复字段。迁移前的评估 JSON 可从本仓库旧 revision 获取。文件中的服务器绝对路径属于运行时记录；迁移后执行代码时需按新环境设置数据和基座模型位置。
数据索引中的 source_file 使用相对于索引目录的 ../raw/HuggingFaceFW-fineweb/sample-10BT/*.parquet 路径。本仓库目前只保存索引，不包含 FineWeb 正文；要重新读取样本，需要将所引用的 FineWeb sample/10BT Parquet 文件放入项目根目录的 data/raw/HuggingFaceFW-fineweb/sample-10BT/，并确认所用源文件与原实验一致。十组实验的冻结基座来自 Qwen/Qwen3-4B-Instruct-2507，本仓库不重复保存基座权重。
实验代码、配置与研究说明见上述 GitHub 项目；各 run 的具体配置快照和 Git 提交记录保存在本仓库对应的 plan/、run.json 和 provenance.json 中。
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