Dataset Preview
Duplicate
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed
Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
elapsed_seconds: double
eligible_directions: int64
heldout_target: string
source_hashes_unchanged: bool
status: string
positive_info: list<item: struct<length: int64, rollout_index: int64>>
  child 0, item: struct<length: int64, rollout_index: int64>
      child 0, length: int64
      child 1, rollout_index: int64
sha256: string
identity: string
min_eigenvalue: double
negative_info: list<item: struct<end: int64, length: int64, response_length: int64, rollout_index: int64, start: in (... 5 chars omitted)
  child 0, item: struct<end: int64, length: int64, response_length: int64, rollout_index: int64, start: int64>
      child 0, end: int64
      child 1, length: int64
      child 2, response_length: int64
      child 3, rollout_index: int64
      child 4, start: int64
to
{'identity': Value('string'), 'min_eigenvalue': Value('float64'), 'negative_info': List({'end': Value('int64'), 'length': Value('int64'), 'response_length': Value('int64'), 'rollout_index': Value('int64'), 'start': Value('int64')}), 'positive_info': List({'length': Value('int64'), 'rollout_index': Value('int64')}), 'sha256': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1827, in _prepare_split_single
                  for key, table in generator:
                                    ^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
                  for item in generator(*args, **kwargs):
                              ~~~~~~~~~^^^^^^^^^^^^^^^^^
                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
              elapsed_seconds: double
              eligible_directions: int64
              heldout_target: string
              source_hashes_unchanged: bool
              status: string
              positive_info: list<item: struct<length: int64, rollout_index: int64>>
                child 0, item: struct<length: int64, rollout_index: int64>
                    child 0, length: int64
                    child 1, rollout_index: int64
              sha256: string
              identity: string
              min_eigenvalue: double
              negative_info: list<item: struct<end: int64, length: int64, response_length: int64, rollout_index: int64, start: in (... 5 chars omitted)
                child 0, item: struct<end: int64, length: int64, response_length: int64, rollout_index: int64, start: int64>
                    child 0, end: int64
                    child 1, length: int64
                    child 2, response_length: int64
                    child 3, rollout_index: int64
                    child 4, start: int64
              to
              {'identity': Value('string'), 'min_eigenvalue': Value('float64'), 'negative_info': List({'end': Value('int64'), 'length': Value('int64'), 'response_length': Value('int64'), 'rollout_index': Value('int64'), 'start': Value('int64')}), 'positive_info': List({'length': Value('int64'), 'rollout_index': Value('int64')}), 'sha256': Value('string')}
              because column names don't match
              
              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/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1880, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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.

identity
string
min_eigenvalue
float64
negative_info
list
positive_info
list
sha256
string
b1e77b732a7af854594f68bc093a39eb83d41c3f0ec70ea3e63622c0ec9d9577
0
[ { "end": 470, "length": 470, "response_length": 3072, "rollout_index": 0, "start": 0 }, { "end": 689, "length": 219, "response_length": 3072, "rollout_index": 0, "start": 470 }, { "end": 713, "length": 24, "response_length": 3072, "rollout_index": 0, ...
[ { "length": 1421, "rollout_index": 2 }, { "length": 941, "rollout_index": 3 }, { "length": 943, "rollout_index": 10 }, { "length": 1417, "rollout_index": 13 }, { "length": 1419, "rollout_index": 16 }, { "length": 1449, "rollout_index": 21 }, { ...
dbf857862851a80a32f5ae2a8181dbe0606bc6df791510a7a2e27ec46865c613
e91c7f79c8a3b3844f61645cafa3fea62678e716feb416fbcfe6c9210f38a130
-0
[ { "end": 59, "length": 59, "response_length": 298, "rollout_index": 0, "start": 0 }, { "end": 141, "length": 82, "response_length": 298, "rollout_index": 0, "start": 59 }, { "end": 204, "length": 63, "response_length": 298, "rollout_index": 0, "sta...
[ { "length": 305, "rollout_index": 4 }, { "length": 323, "rollout_index": 19 } ]
6a875ad8061f6eec76e88d5ac6c48b61d80bcd1c18aa2e30df8e2d609b8aa6e6
0a69a2fdbf175855986d7a732b31e28697915db713b0c898c7ebf813e1457249
-0
[ { "end": 65, "length": 65, "response_length": 3072, "rollout_index": 0, "start": 0 }, { "end": 119, "length": 54, "response_length": 3072, "rollout_index": 0, "start": 65 }, { "end": 271, "length": 152, "response_length": 3072, "rollout_index": 0, ...
[ { "length": 3072, "rollout_index": 20 } ]
bcddd0f6dd5cbc7712f0dd82621db4d8b5ca6f3e18927311f32874dcb385afb5
7700dbb94d06df78b7322aacbebd68ca66047044deed52e59c00bf91bf9987d9
0.000028
[ { "end": 48, "length": 48, "response_length": 3072, "rollout_index": 20, "start": 0 }, { "end": 67, "length": 19, "response_length": 3072, "rollout_index": 20, "start": 48 }, { "end": 120, "length": 53, "response_length": 3072, "rollout_index": 20, ...
[ { "length": 368, "rollout_index": 0 }, { "length": 356, "rollout_index": 1 }, { "length": 360, "rollout_index": 2 }, { "length": 334, "rollout_index": 3 }, { "length": 363, "rollout_index": 4 }, { "length": 325, "rollout_index": 5 }, { "len...
8582b46a4e798f1c9afe0716a309713581527d4e676c03aee337b9d169fe54e2
66bb10986caedf5fe9df018a3eebac773cebae9cac413a7f0a0ed17650028e59
0
[ { "end": 66, "length": 66, "response_length": 515, "rollout_index": 0, "start": 0 }, { "end": 88, "length": 22, "response_length": 515, "rollout_index": 0, "start": 66 }, { "end": 124, "length": 36, "response_length": 515, "rollout_index": 0, "star...
[ { "length": 569, "rollout_index": 1 }, { "length": 494, "rollout_index": 2 }, { "length": 385, "rollout_index": 5 }, { "length": 492, "rollout_index": 6 }, { "length": 502, "rollout_index": 8 }, { "length": 480, "rollout_index": 11 }, { "le...
b0b7ee9093b93c75f68750b254d98129d77ea204d870b9f2f22cc050c999c0d9
6b9824c6659bfc7e0f9c9bc029abe6270747e779838cc9fbd335eb0e8f97a7d0
-0
[ { "end": 35, "length": 35, "response_length": 3072, "rollout_index": 2, "start": 0 }, { "end": 83, "length": 48, "response_length": 3072, "rollout_index": 2, "start": 35 }, { "end": 144, "length": 61, "response_length": 3072, "rollout_index": 2, "s...
[ { "length": 689, "rollout_index": 0 }, { "length": 512, "rollout_index": 1 }, { "length": 612, "rollout_index": 3 }, { "length": 535, "rollout_index": 4 }, { "length": 475, "rollout_index": 5 }, { "length": 523, "rollout_index": 6 }, { "len...
7eba059048bd565d12c5f943a183f23a897919eb8d0a11cb25b117e3ece61248
7bc2dce9c16197ac176808295ada195a8a74d805cf190889b6005e5b4443bff1
-0
[ { "end": 39, "length": 39, "response_length": 3072, "rollout_index": 3, "start": 0 }, { "end": 104, "length": 65, "response_length": 3072, "rollout_index": 3, "start": 39 }, { "end": 183, "length": 79, "response_length": 3072, "rollout_index": 3, "...
[ { "length": 530, "rollout_index": 0 }, { "length": 349, "rollout_index": 1 }, { "length": 334, "rollout_index": 2 }, { "length": 325, "rollout_index": 4 }, { "length": 428, "rollout_index": 5 }, { "length": 263, "rollout_index": 6 }, { "len...
b739935f16b4e2ce2ec6837bd860050d25e13aa31da8fdc669013a40a2452563
99ded5dfe7846a638c673a225fa1ae271ca112ef76afce3d662235053c3230fa
0.000096
[{"end":460,"length":460,"response_length":3072,"rollout_index":1,"start":0},{"end":534,"length":74,(...TRUNCATED)
[{"length":1139,"rollout_index":0},{"length":1003,"rollout_index":3},{"length":1095,"rollout_index":(...TRUNCATED)
05aff2a45f4cce3241794ea1d08b9cbbbe72601d27848d48a9c4a8841a72788b
319ed27e3d6db611b50fcb912cbfd630e5c7649b03e1fe4bf742babff90dd567
0.009324
[{"end":204,"length":204,"response_length":3072,"rollout_index":2,"start":0},{"end":397,"length":193(...TRUNCATED)
[{"length":360,"rollout_index":0},{"length":351,"rollout_index":1},{"length":344,"rollout_index":4},(...TRUNCATED)
3094d5eb571e3ae8ae691aa8d2e317ecb9ad033e5bb3c86beb27992fffa45f41
efff32d1dd51fb5f165e0af6c2a396e6194775bac8abf8c60ff9b18b48621da3
0.021104
[{"end":11,"length":11,"response_length":3072,"rollout_index":22,"start":0},{"end":50,"length":39,"r(...TRUNCATED)
[{"length":320,"rollout_index":0},{"length":312,"rollout_index":1},{"length":261,"rollout_index":2},(...TRUNCATED)
cafe3860487e3b92fa33bab72a0e5d57edce9fbee5c6ad907d500f6f473e33ec
End of preview.

my_gpro examples ver2

Snapshot of /root/my_gpro/examples in the private dataset repository AnhLD2610/ver2. The contents of the local examples directory are at this repository's root.

This version includes example scripts, Nash experiment code, diagnostic reports, features, rollout data, runtime caches, worker outputs, and unmerged partial artifacts present in the source snapshot. Source contents are preserved as supplied.

upload_manifest.json lists every included original file, its size, SHA-256 checksum, storage location, and all omitted transient files. Omitted files are limited to standard .git, __pycache__, .pytest_cache, .mypy_cache, .ruff_cache, .cache, .venv, venv, and node_modules directories; .pyc and .pyo files; and .stage.lock and .DS_Store files.

Restore rollout parts

Both diagnostic round directories have rollout_parts trees containing 16,000 files per split directory. Each tree, including its generation_identity.json, is preserved in a sibling rollout_parts.tar.gz. This keeps repository directories within Hugging Face's entry limit. Every archived file was verified against its original size and SHA-256 checksum. Other files retain their original relative paths.

The archives are:

  • nash_exp/artifacts/diagnostic_b/round1_qwen25math7b_instruct_math500_test500_p1024_g3072/rollout_parts.tar.gz
  • nash_exp/artifacts/diagnostic_b/round1_qwen3_4b_nonthinking_math500_test500_p2048_g30000/rollout_parts.tar.gz

From the downloaded repository root, restore both original rollout-part trees with:

for archive in nash_exp/artifacts/diagnostic_b/*/rollout_parts.tar.gz; do
    tar -xzf "$archive" -C "$(dirname "$archive")"
done

The existing train_rollouts.jsonl.zst and heldout_rollouts.jsonl.zst files are also included unchanged.

Downloads last month
6