Dataset Viewer
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: CastError
Message: Couldn't cast
doc_id: int64
doc: struct<path: string, signature: string, doc: string, change_type: string, entry_type: string, instru (... 246 chars omitted)
child 0, path: string
child 1, signature: string
child 2, doc: string
child 3, change_type: string
child 4, entry_type: string
child 5, instruction: string
child 6, after: string
child 7, before: string
child 8, full_code: string
child 9, teacher_model: string
child 10, teacher_example_index: string
child 11, teacher_prompt: string
child 12, api_usage_match_method: string
child 13, api_usage_strict_matches: string
child 14, api_usage_short_name_matches: string
target: string
arguments: struct<gen_args_0: struct<arg_0: string, arg_1: struct<until: list<item: string>, do_sample: bool, m (... 65 chars omitted)
child 0, gen_args_0: struct<arg_0: string, arg_1: struct<until: list<item: string>, do_sample: bool, max_gen_toks: int64, (... 45 chars omitted)
child 0, arg_0: string
child 1, arg_1: struct<until: list<item: string>, do_sample: bool, max_gen_toks: int64, max_new_tokens: int64, tempe (... 15 chars omitted)
child 0, until: list<item: string>
child 0, item: string
child 1, do_sample: bool
child 2, max_gen_toks: int64
child 3, max_new_tokens: int64
child 4, temperature: double
resps: list<item: list<item: string>>
child 0, item: list<item: string>
child 0, item: string
filtered_resps: list<item: string>
child 0, item:
...
: double
child 9, id_precision,none: double
child 10, id_precision_stderr,none: double
child 11, id_recall,none: double
child 12, id_recall_stderr,none: double
child 13, id_ns_f1,none: double
child 14, id_ns_f1_stderr,none: double
child 15, id_ns_precision,none: double
child 16, id_ns_precision_stderr,none: double
child 17, id_ns_recall,none: double
child 18, id_ns_recall_stderr,none: double
group_subtasks: struct<eval_on_training: list<item: null>>
child 0, eval_on_training: list<item: null>
child 0, item: null
task_hashes: struct<eval_on_training: string>
child 0, eval_on_training: string
fewshot_as_multiturn: null
system_instruction_sha: null
system_instruction: null
chat_template: null
n-samples: struct<eval_on_training: struct<original: int64, effective: int64>>
child 0, eval_on_training: struct<original: int64, effective: int64>
child 0, original: int64
child 1, effective: int64
lm_eval_version: string
chat_template_sha: null
git_hash: string
total_evaluation_time_seconds: string
higher_is_better: struct<eval_on_training: struct<id_f1: bool, exact_match: bool, edit_similarity: bool, id_exact_matc (... 9 chars omitted)
child 0, eval_on_training: struct<id_f1: bool, exact_match: bool, edit_similarity: bool, id_exact_match: bool>
child 0, id_f1: bool
child 1, exact_match: bool
child 2, edit_similarity: bool
child 3, id_exact_match: bool
transformers_version: string
to
{'results': {'eval_on_training': {'alias': Value('string'), 'id_f1,none': Value('float64'), 'id_f1_stderr,none': Value('float64'), 'exact_match,none': Value('float64'), 'exact_match_stderr,none': Value('float64'), 'edit_similarity,none': Value('float64'), 'edit_similarity_stderr,none': Value('float64'), 'id_exact_match,none': Value('float64'), 'id_exact_match_stderr,none': Value('float64'), 'id_precision,none': Value('float64'), 'id_precision_stderr,none': Value('float64'), 'id_recall,none': Value('float64'), 'id_recall_stderr,none': Value('float64'), 'id_ns_f1,none': Value('float64'), 'id_ns_f1_stderr,none': Value('float64'), 'id_ns_precision,none': Value('float64'), 'id_ns_precision_stderr,none': Value('float64'), 'id_ns_recall,none': Value('float64'), 'id_ns_recall_stderr,none': Value('float64')}}, 'group_subtasks': {'eval_on_training': List(Value('null'))}, 'configs': {'eval_on_training': {'task': Value('string'), 'tag': List(Value('string')), 'dataset_path': Value('string'), 'dataset_name': Value('string'), 'test_split': Value('string'), 'fewshot_split': Value('string'), 'doc_to_text': Value('string'), 'doc_to_target': Value('string'), 'unsafe_code': Value('bool'), 'process_results': Value('string'), 'description': Value('string'), 'target_delimiter': Value('string'), 'fewshot_delimiter': Value('string'), 'fewshot_config': {'sampler': Value('string'), 'split': Value('string'), 'process_docs': Value('null'), 'fewshot_indices': Value('null'), 'samples': Value('null'), 'doc
...
string'), 'base_url': Value('string'), 'tokenized_requests': Value('bool')}}}, 'versions': {'eval_on_training': Value('float64')}, 'n-shot': {'eval_on_training': Value('int64')}, 'higher_is_better': {'eval_on_training': {'id_f1': Value('bool'), 'exact_match': Value('bool'), 'edit_similarity': Value('bool'), 'id_exact_match': Value('bool')}}, 'n-samples': {'eval_on_training': {'original': Value('int64'), 'effective': Value('int64')}}, 'config': {'model': Value('string'), 'model_args': {'model': Value('string'), 'base_url': Value('string'), 'tokenized_requests': Value('bool')}, 'batch_size': Value('string'), 'batch_sizes': List(Value('null')), 'device': Value('string'), 'use_cache': Value('null'), 'limit': Value('null'), 'bootstrap_iters': Value('int64'), 'gen_kwargs': {}, 'random_seed': Value('int64'), 'numpy_seed': Value('int64'), 'torch_seed': Value('int64'), 'fewshot_seed': Value('int64')}, 'git_hash': Value('string'), 'date': Value('float64'), 'pretty_env_info': Value('string'), 'transformers_version': Value('string'), 'lm_eval_version': Value('string'), 'upper_git_hash': Value('null'), 'task_hashes': {'eval_on_training': Value('string')}, 'model_source': Value('string'), 'model_name': Value('string'), 'model_name_sanitized': Value('string'), 'system_instruction': Value('null'), 'system_instruction_sha': Value('null'), 'fewshot_as_multiturn': Value('null'), 'chat_template': Value('null'), 'chat_template_sha': Value('null'), 'total_evaluation_time_seconds': Value('string')}
because column names don't match
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 478, 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 2818, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, 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 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
doc_id: int64
doc: struct<path: string, signature: string, doc: string, change_type: string, entry_type: string, instru (... 246 chars omitted)
child 0, path: string
child 1, signature: string
child 2, doc: string
child 3, change_type: string
child 4, entry_type: string
child 5, instruction: string
child 6, after: string
child 7, before: string
child 8, full_code: string
child 9, teacher_model: string
child 10, teacher_example_index: string
child 11, teacher_prompt: string
child 12, api_usage_match_method: string
child 13, api_usage_strict_matches: string
child 14, api_usage_short_name_matches: string
target: string
arguments: struct<gen_args_0: struct<arg_0: string, arg_1: struct<until: list<item: string>, do_sample: bool, m (... 65 chars omitted)
child 0, gen_args_0: struct<arg_0: string, arg_1: struct<until: list<item: string>, do_sample: bool, max_gen_toks: int64, (... 45 chars omitted)
child 0, arg_0: string
child 1, arg_1: struct<until: list<item: string>, do_sample: bool, max_gen_toks: int64, max_new_tokens: int64, tempe (... 15 chars omitted)
child 0, until: list<item: string>
child 0, item: string
child 1, do_sample: bool
child 2, max_gen_toks: int64
child 3, max_new_tokens: int64
child 4, temperature: double
resps: list<item: list<item: string>>
child 0, item: list<item: string>
child 0, item: string
filtered_resps: list<item: string>
child 0, item:
...
: double
child 9, id_precision,none: double
child 10, id_precision_stderr,none: double
child 11, id_recall,none: double
child 12, id_recall_stderr,none: double
child 13, id_ns_f1,none: double
child 14, id_ns_f1_stderr,none: double
child 15, id_ns_precision,none: double
child 16, id_ns_precision_stderr,none: double
child 17, id_ns_recall,none: double
child 18, id_ns_recall_stderr,none: double
group_subtasks: struct<eval_on_training: list<item: null>>
child 0, eval_on_training: list<item: null>
child 0, item: null
task_hashes: struct<eval_on_training: string>
child 0, eval_on_training: string
fewshot_as_multiturn: null
system_instruction_sha: null
system_instruction: null
chat_template: null
n-samples: struct<eval_on_training: struct<original: int64, effective: int64>>
child 0, eval_on_training: struct<original: int64, effective: int64>
child 0, original: int64
child 1, effective: int64
lm_eval_version: string
chat_template_sha: null
git_hash: string
total_evaluation_time_seconds: string
higher_is_better: struct<eval_on_training: struct<id_f1: bool, exact_match: bool, edit_similarity: bool, id_exact_matc (... 9 chars omitted)
child 0, eval_on_training: struct<id_f1: bool, exact_match: bool, edit_similarity: bool, id_exact_match: bool>
child 0, id_f1: bool
child 1, exact_match: bool
child 2, edit_similarity: bool
child 3, id_exact_match: bool
transformers_version: string
to
{'results': {'eval_on_training': {'alias': Value('string'), 'id_f1,none': Value('float64'), 'id_f1_stderr,none': Value('float64'), 'exact_match,none': Value('float64'), 'exact_match_stderr,none': Value('float64'), 'edit_similarity,none': Value('float64'), 'edit_similarity_stderr,none': Value('float64'), 'id_exact_match,none': Value('float64'), 'id_exact_match_stderr,none': Value('float64'), 'id_precision,none': Value('float64'), 'id_precision_stderr,none': Value('float64'), 'id_recall,none': Value('float64'), 'id_recall_stderr,none': Value('float64'), 'id_ns_f1,none': Value('float64'), 'id_ns_f1_stderr,none': Value('float64'), 'id_ns_precision,none': Value('float64'), 'id_ns_precision_stderr,none': Value('float64'), 'id_ns_recall,none': Value('float64'), 'id_ns_recall_stderr,none': Value('float64')}}, 'group_subtasks': {'eval_on_training': List(Value('null'))}, 'configs': {'eval_on_training': {'task': Value('string'), 'tag': List(Value('string')), 'dataset_path': Value('string'), 'dataset_name': Value('string'), 'test_split': Value('string'), 'fewshot_split': Value('string'), 'doc_to_text': Value('string'), 'doc_to_target': Value('string'), 'unsafe_code': Value('bool'), 'process_results': Value('string'), 'description': Value('string'), 'target_delimiter': Value('string'), 'fewshot_delimiter': Value('string'), 'fewshot_config': {'sampler': Value('string'), 'split': Value('string'), 'process_docs': Value('null'), 'fewshot_indices': Value('null'), 'samples': Value('null'), 'doc
...
string'), 'base_url': Value('string'), 'tokenized_requests': Value('bool')}}}, 'versions': {'eval_on_training': Value('float64')}, 'n-shot': {'eval_on_training': Value('int64')}, 'higher_is_better': {'eval_on_training': {'id_f1': Value('bool'), 'exact_match': Value('bool'), 'edit_similarity': Value('bool'), 'id_exact_match': Value('bool')}}, 'n-samples': {'eval_on_training': {'original': Value('int64'), 'effective': Value('int64')}}, 'config': {'model': Value('string'), 'model_args': {'model': Value('string'), 'base_url': Value('string'), 'tokenized_requests': Value('bool')}, 'batch_size': Value('string'), 'batch_sizes': List(Value('null')), 'device': Value('string'), 'use_cache': Value('null'), 'limit': Value('null'), 'bootstrap_iters': Value('int64'), 'gen_kwargs': {}, 'random_seed': Value('int64'), 'numpy_seed': Value('int64'), 'torch_seed': Value('int64'), 'fewshot_seed': Value('int64')}, 'git_hash': Value('string'), 'date': Value('float64'), 'pretty_env_info': Value('string'), 'transformers_version': Value('string'), 'lm_eval_version': Value('string'), 'upper_git_hash': Value('null'), 'task_hashes': {'eval_on_training': Value('string')}, 'model_source': Value('string'), 'model_name': Value('string'), 'model_name_sanitized': Value('string'), 'system_instruction': Value('null'), 'system_instruction_sha': Value('null'), 'fewshot_as_multiturn': Value('null'), 'chat_template': Value('null'), 'chat_template_sha': Value('null'), 'total_evaluation_time_seconds': Value('string')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
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