Datasets:

VenusChenyy
/

RULER_50

Tasks:

Text Generation

Languages:

English

License:

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xet

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The dataset generation failed

Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
created_utc: timestamp[s]
source_root: string
output_root: string
source_layout: string
output_layout: string
context_lengths: list<item: int64>
  child 0, item: int64
datasets_requested: list<item: string>
  child 0, item: string
samples_per_file: int64
selection: string
files: list<item: struct<dataset: string, context_length: int64, source_path: string, output_path: string,  (... 113 chars omitted)
  child 0, item: struct<dataset: string, context_length: int64, source_path: string, output_path: string, source_rows (... 101 chars omitted)
      child 0, dataset: string
      child 1, context_length: int64
      child 2, source_path: string
      child 3, output_path: string
      child 4, source_rows: int64
      child 5, sampled_rows: int64
      child 6, source_positions: list<item: int64>
          child 0, item: int64
      child 7, source_indices: list<item: int64>
          child 0, item: int64
missing_files: list<item: null>
  child 0, item: null
length_w_model_temp: int64
outputs: list<item: string>
  child 0, item: string
index: int64
length: int64
input: string
answer_prefix: string
to
{'index': Value('int64'), 'input': Value('string'), 'outputs': List(Value('string')), 'length': Value('int64'), 'length_w_model_temp': Value('int64'), 'answer_prefix': 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 1816, 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 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              created_utc: timestamp[s]
              source_root: string
              output_root: string
              source_layout: string
              output_layout: string
              context_lengths: list<item: int64>
                child 0, item: int64
              datasets_requested: list<item: string>
                child 0, item: string
              samples_per_file: int64
              selection: string
              files: list<item: struct<dataset: string, context_length: int64, source_path: string, output_path: string,  (... 113 chars omitted)
                child 0, item: struct<dataset: string, context_length: int64, source_path: string, output_path: string, source_rows (... 101 chars omitted)
                    child 0, dataset: string
                    child 1, context_length: int64
                    child 2, source_path: string
                    child 3, output_path: string
                    child 4, source_rows: int64
                    child 5, sampled_rows: int64
                    child 6, source_positions: list<item: int64>
                        child 0, item: int64
                    child 7, source_indices: list<item: int64>
                        child 0, item: int64
              missing_files: list<item: null>
                child 0, item: null
              length_w_model_temp: int64
              outputs: list<item: string>
                child 0, item: string
              index: int64
              length: int64
              input: string
              answer_prefix: string
              to
              {'index': Value('int64'), 'input': Value('string'), 'outputs': List(Value('string')), 'length': Value('int64'), 'length_w_model_temp': Value('int64'), 'answer_prefix': 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 1683, 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 1869, 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

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index int64	input string	outputs list	length int64	length_w_model_temp int64	answer_prefix string
5	"Below is a numbered list of words. In these words, some appear more often than others. Memorize the(...TRUNCATED)	["allocation","sleeping","tutor","agony","trowel","siding","influence","baseboard","condominium","oc(...TRUNCATED)	130,702	130,702	Answer: The top 10 words that appear most often in the list are:
15	"Below is a numbered list of words. In these words, some appear more often than others. Memorize the(...TRUNCATED)	["bather","tights","creativity","candelabra","fierce","harp","clarity","numberless","pyridine","punc(...TRUNCATED)	130,493	130,493	Answer: The top 10 words that appear most often in the list are:
25	"Below is a numbered list of words. In these words, some appear more often than others. Memorize the(...TRUNCATED)	[ "glossy", "military", "gripper", "terminal", "wine", "donation", "dazzling", "arrive", "chest", "undress" ]	130,582	130,582	Answer: The top 10 words that appear most often in the list are:
35	"Below is a numbered list of words. In these words, some appear more often than others. Memorize the(...TRUNCATED)	["file","separate","survey","cupola","stingy","penalty","recall","chafe","congressperson","incompete(...TRUNCATED)	130,799	130,799	Answer: The top 10 words that appear most often in the list are:
45	"Below is a numbered list of words. In these words, some appear more often than others. Memorize the(...TRUNCATED)	["balance","swallow","promotion","pegboard","mime","enactment","howitzer","nightlight","adult","wool(...TRUNCATED)	130,751	130,751	Answer: The top 10 words that appear most often in the list are:
55	"Below is a numbered list of words. In these words, some appear more often than others. Memorize the(...TRUNCATED)	["colorful","clogs","volleyball","rhetoric","maternity","secure","opportunity","ugly","chapter","tog(...TRUNCATED)	130,871	130,871	Answer: The top 10 words that appear most often in the list are:
65	"Below is a numbered list of words. In these words, some appear more often than others. Memorize the(...TRUNCATED)	["semester","carbohydrate","handball","assignment","soothe","doe","rob","nutrient","casserole","syst(...TRUNCATED)	131,036	131,036	Answer: The top 10 words that appear most often in the list are:
75	"Below is a numbered list of words. In these words, some appear more often than others. Memorize the(...TRUNCATED)	[ "approve", "futon", "library", "deserted", "watery", "core", "constraint", "capitalism", "port", "veto" ]	130,789	130,789	Answer: The top 10 words that appear most often in the list are:
85	"Below is a numbered list of words. In these words, some appear more often than others. Memorize the(...TRUNCATED)	[ "tree", "bed", "mortal", "bit", "imagine", "toot", "associate", "sesame", "antigen", "scrawny" ]	130,953	130,953	Answer: The top 10 words that appear most often in the list are:
95	"Below is a numbered list of words. In these words, some appear more often than others. Memorize the(...TRUNCATED)	[ "snowman", "monk", "reject", "squid", "rumor", "parsnip", "cruelty", "invent", "mine", "oleo" ]	130,876	130,876	Answer: The top 10 words that appear most often in the list are:

End of preview.

RULER_50 Official-Code Qwen3 Subset

This dataset is a fixed 50-sample-per-group subset of RULER synthetic tasks. It was generated from the official NVIDIA/RULER GitHub code, not from a third-party pre-generated mirror.

Official generation source:

Repository: https://github.com/NVIDIA/RULER
Branch: main
Commit: 38da79d79519ef87aa46ae804f838e1eab7f86d7
Generation entrypoint: scripts/data/prepare.py
Benchmark config: scripts/synthetic.yaml

Generation settings:

tokenizer: /scratch/yc7009/models/Qwen3-4B-Instruct-2507
tokenizer_type: hf
model_template_type: base
num_samples: 500
random_seed: 42
context_lengths: 4096,8192,16384,32768,65536,131072
tasks: 13 official RULER synthetic tasks

Official source files were first generated as:

RULER/data/official/<task>/<context_length>.jsonl

Each source file contains 500 generated examples. This dataset then samples 50 examples from each 500-example source file using deterministic stratified_midpoint positions:

5,15,25,...,495

The uploaded subset layout is task-first:

<task>/<context_length>.jsonl

Each JSONL row also includes task as its first field, matching the parent task directory, so downstream dataset loaders can index by task without parsing file paths.

Coverage:

tasks: 13
context lengths per task: 6
files: 78
rows per file: 50
total rows: 3900

Tasks:

niah_single_1
niah_single_2
niah_single_3
niah_multikey_1
niah_multikey_2
niah_multikey_3
niah_multivalue
niah_multiquery
vt
cwe
fwe
qa_1
qa_2

Context lengths:

Included provenance files:

manifest.json
source_official_generation_manifest.json

manifest.json records the 50-sample extraction from the generated official source. source_official_generation_manifest.json records the full NVIDIA/RULER official-code source generation.

Downloads last month: 132

Total file size:

624 MB