| dataset_info: | |
| features: | |
| - name: prompt_text | |
| dtype: string | |
| - name: prompt_ids | |
| sequence: int64 | |
| - name: decode_ids | |
| sequence: int64 | |
| - name: prompt_pattern | |
| sequence: | |
| sequence: int64 | |
| - name: decode_pattern | |
| sequence: | |
| sequence: int64 | |
| splits: | |
| - name: train | |
| num_bytes: 483379455 | |
| num_examples: 32808 | |
| download_size: 46650593 | |
| dataset_size: 483379455 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/train-* | |
| - prompt_ids: `[ 1593, 10, 3547, 6180, 7836, 489, 33, 66, 1 ]` | |
| - prompt_pattern: `[ [ 14, 12, 17, 17, 17, 17, 10, 4, 12 ], [ 15, 17, 18, 18, 18, 5, 21, 12, 15 ], [ 2, 7, 22, 23, 23, 23, 31, 2, 31 ], [ 8, 8, 2, 2, 2, 2, 28, 7, 8 ], [ 0, 12, 7, 13, 13, 7, 11, 8, 11 ], [ 2, 19, 14, 8, 14, 14, 13, 16, 4 ] ]` | |
| [ 14, 12, 17, 17, 17, 17, 10, 4, 12 ]表示 9 个 prompt ids 在encoder第一个moe 层激活的 expert 索引值。例如 token 1593 在encoder 第一层moe 激活的 expert 是 14. |