The dataset viewer is not available for this dataset.
Cannot get the config names for the dataset.
Error code:   ConfigNamesError
Exception:    DataFilesNotFoundError
Message:      No (supported) data files found in nodchip/shogi_suisho5_depth9_entering_king
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 67, in compute_config_names_response
                  get_dataset_config_names(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 347, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1865, in dataset_module_factory
                  raise e1 from None
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1846, in dataset_module_factory
                  return HubDatasetModuleFactoryWithoutScript(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1240, in get_module
                  module_name, default_builder_kwargs = infer_module_for_data_files(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 592, in infer_module_for_data_files
                  raise DataFilesNotFoundError("No (supported) data files found" + (f" in {path}" if path else ""))
              datasets.exceptions.DataFilesNotFoundError: No (supported) data files found in nodchip/shogi_suisho5_depth9_entering_king

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Summary

Training Data for Shogi AI Development

Contents

  • kifu.tag=suisho5.entering_king.depth=9.num_positions=500000000.start_time=??????????.thread_index=???.bin ... Training Data

The training data are provided in the YaneuraOu PackedSfenValue format.

This dataset was generated using Suisho5 with a search depth of 9. The starting positions were selectively chosen from Floodgate games spanning the years 2015 to 2024, specifically focusing on scenarios involving entering king positions.

The training data have not been shuffled. It is recommended to shuffle the training data before use. Additionally, positions within this dataset have not been replaced with the PV (Principal Variation) leaf node from the quiescence search of the original position. Users are advised to consider applying such modifications as needed for their specific use case.

Links

  • nodchip/tanuki-: shogi engine(AI player), stronger than Bonanza6 , educational and tiny code(about 2500 lines) , USI compliant engine , capable of being compiled by VC++2015 https://github.com/nodchip/tanuki-
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