qleap/Training_dataset_by_NAGISA_V4
NAGISA_V4 ply-37 teacher shards, games played to the end Self-play of attic-gensfen reading the NNUE weights NAGISA_V4 (HalfKA-2304), in the shape the trainers read directly. Every game starts from a balanced ply-37 position, makes no random moves, and runs until it actually ends. Identical positions are folded into one row each. 67,108,864 rows — exactly 2^26 16 shards of 4,194,304 rows, 512 row groups each, zstd, 5,208,620,326 B total Against Opening_dataset_by_NAGISA_V4… See the full description on the dataset page: https://huggingface.co/datasets/qleap/Training_dataset_by_NAGISA_V4.
Drop machine-specific paths from the card (card)
Trim the dataset card to what a reader of the shards needs (card)
Publish ply-37 played-out teacher shards (2^26 rows, with value_z) (card)
Publish ply-37 played-out teacher shards (2^26 rows, with value_z)
initial commit