| language: | |
| - en | |
| dataset_info: | |
| features: | |
| - name: prompt | |
| dtype: string | |
| - name: answer | |
| dtype: string | |
| splits: | |
| - name: spell | |
| num_bytes: 465046 | |
| num_examples: 1000 | |
| - name: spell_inverse | |
| num_bytes: 446046 | |
| num_examples: 1000 | |
| - name: contains_char | |
| num_bytes: 424176 | |
| num_examples: 1000 | |
| - name: contains_word | |
| num_bytes: 530494 | |
| num_examples: 1000 | |
| - name: orth | |
| num_bytes: 607118 | |
| num_examples: 1000 | |
| - name: sem | |
| num_bytes: 608098 | |
| num_examples: 1000 | |
| - name: ins_char | |
| num_bytes: 560474 | |
| num_examples: 1000 | |
| - name: ins_word | |
| num_bytes: 775597 | |
| num_examples: 1000 | |
| - name: del_char | |
| num_bytes: 513247 | |
| num_examples: 1000 | |
| - name: del_word | |
| num_bytes: 689114 | |
| num_examples: 1000 | |
| - name: sub_char | |
| num_bytes: 532364 | |
| num_examples: 1000 | |
| - name: sub_word | |
| num_bytes: 743529 | |
| num_examples: 1000 | |
| - name: swap_char | |
| num_bytes: 470394 | |
| num_examples: 1000 | |
| - name: swap_word | |
| num_bytes: 675168 | |
| num_examples: 1000 | |
| download_size: 962103 | |
| dataset_size: 8040865 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: spell | |
| path: data/spell-* | |
| - split: spell_inverse | |
| path: data/spell_inverse-* | |
| - split: contains_char | |
| path: data/contains_char-* | |
| - split: contains_word | |
| path: data/contains_word-* | |
| - split: orth | |
| path: data/orth-* | |
| - split: sem | |
| path: data/sem-* | |
| - split: ins_char | |
| path: data/ins_char-* | |
| - split: ins_word | |
| path: data/ins_word-* | |
| - split: del_char | |
| path: data/del_char-* | |
| - split: del_word | |
| path: data/del_word-* | |
| - split: sub_char | |
| path: data/sub_char-* | |
| - split: sub_word | |
| path: data/sub_word-* | |
| - split: swap_char | |
| path: data/swap_char-* | |
| - split: swap_word | |
| path: data/swap_word-* | |
| # CUTE | |
| Here is the CUTE benchmark, a benchmark designed for testing LLM's ability to understand the characters within their tokens. | |
| To use this dataset as we did, make sure to use ``` tokenizer.apply_chat_template ``` on the prompt, and then add ``` Answer: " ``` afterwards to the resulting string. | |
| For smaller LLMs, you may need to do some post-processing on the final answer. | |
| You can also check out our implementation at: https://github.com/Leukas/cute |