Fix YAML error in README files appearing on GitHub
Opened by albertvillanova (closed)

Fix YAML error in README files appearing on GitHub.

See error message:
![Screenshot from 2024-05-14 06-58-02](https://github.com/huggingface/datasets/assets/8515462/7984cc4e-96ee-4e83-99a4-4c0c5791fa05)


Fix #6897.

Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6898). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

After this PR, the README file looks like:

![Screenshot from 2024-05-14 14-19-29](https://github.com/huggingface/datasets/assets/8515462/1f665a06-98be-4dd7-ba7e-7cc025489503)


<details>
<summary>Show benchmarks</summary>

PyArrow==8.0.0

<details>
<summary>Show updated benchmarks!</summary>

### Benchmark: benchmark_array_xd.json

| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.004936 / 0.011353 (-0.006417) | 0.003591 / 0.011008 (-0.007418) | 0.062967 / 0.038508 (0.024459) | 0.031314 / 0.023109 (0.008205) | 0.248040 / 0.275898 (-0.027858) | 0.271630 / 0.323480 (-0.051850) | 0.003085 / 0.007986 (-0.004901) | 0.002605 / 0.004328 (-0.001724) | 0.049452 / 0.004250 (0.045202) | 0.044929 / 0.037052 (0.007876) | 0.264254 / 0.258489 (0.005765) | 0.287531 / 0.293841 (-0.006310) | 0.027197 / 0.128546 (-0.101349) | 0.009925 / 0.075646 (-0.065721) | 0.203165 / 0.419271 (-0.216107) | 0.035658 / 0.043533 (-0.007875) | 0.250207 / 0.255139 (-0.004932) | 0.269258 / 0.283200 (-0.013941) | 0.019975 / 0.141683 (-0.121708) | 1.093703 / 1.452155 (-0.358452) | 1.134031 / 1.492716 (-0.358685) |

### Benchmark: benchmark_getitem\_100B.json

| metric | get_batch_of\_1024\_random_rows | get_batch_of\_1024\_rows | get_first_row | get_last_row |
|--------|---|---|---|---|
| new / old (diff) | 0.095089 / 0.018006 (0.077082) | 0.301410 / 0.000490 (0.300920) | 0.000251 / 0.000200 (0.000051) | 0.000047 / 0.000054 (-0.000007) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.018453 / 0.037411 (-0.018958) | 0.061674 / 0.014526 (0.047148) | 0.073442 / 0.176557 (-0.103114) | 0.119743 / 0.737135 (-0.617392) | 0.074518 / 0.296338 (-0.221820) |

### Benchmark: benchmark_iterating.json

| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.276351 / 0.215209 (0.061142) | 2.757670 / 2.077655 (0.680015) | 1.471199 / 1.504120 (-0.032921) | 1.363620 / 1.541195 (-0.177575) | 1.374175 / 1.468490 (-0.094315) | 0.556444 / 4.584777 (-4.028333) | 2.340637 / 3.745712 (-1.405075) | 2.728341 / 5.269862 (-2.541521) | 1.701214 / 4.565676 (-2.864463) | 0.061832 / 0.424275 (-0.362443) | 0.005287 / 0.007607 (-0.002320) | 0.331848 / 0.226044 (0.105804) | 3.334204 / 2.268929 (1.065276) | 1.791203 / 55.444624 (-53.653421) | 1.512246 / 6.876477 (-5.364231) | 1.529570 / 2.142072 (-0.612503) | 0.632193 / 4.805227 (-4.173034) | 0.116512 / 6.500664 (-6.384153) | 0.041271 / 0.075469 (-0.034198) |

### Benchmark: benchmark_map_filter.json

| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |
|--------|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.981813 / 1.841788 (-0.859974) | 11.271398 / 8.074308 (3.197090) | 9.654613 / 10.191392 (-0.536780) | 0.140235 / 0.680424 (-0.540188) | 0.014336 / 0.534201 (-0.519865) | 0.284286 / 0.579283 (-0.294997) | 0.260265 / 0.434364 (-0.174099) | 0.321064 / 0.540337 (-0.219274) | 0.417554 / 1.386936 (-0.969382) |

</details>
PyArrow==latest

<details>
<summary>Show updated benchmarks!</summary>

### Benchmark: benchmark_array_xd.json

| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.005265 / 0.011353 (-0.006088) | 0.003237 / 0.011008 (-0.007772) | 0.049723 / 0.038508 (0.011215) | 0.031705 / 0.023109 (0.008596) | 0.255548 / 0.275898 (-0.020350) | 0.281651 / 0.323480 (-0.041829) | 0.004099 / 0.007986 (-0.003886) | 0.002739 / 0.004328 (-0.001589) | 0.049713 / 0.004250 (0.045463) | 0.041563 / 0.037052 (0.004511) | 0.269500 / 0.258489 (0.011011) | 0.293948 / 0.293841 (0.000107) | 0.029259 / 0.128546 (-0.099287) | 0.010391 / 0.075646 (-0.065255) | 0.057772 / 0.419271 (-0.361500) | 0.033125 / 0.043533 (-0.010408) | 0.258838 / 0.255139 (0.003699) | 0.278616 / 0.283200 (-0.004584) | 0.017543 / 0.141683 (-0.124139) | 1.130319 / 1.452155 (-0.321835) | 1.185976 / 1.492716 (-0.306740) |

### Benchmark: benchmark_getitem\_100B.json

| metric | get_batch_of\_1024\_random_rows | get_batch_of\_1024\_rows | get_first_row | get_last_row |
|--------|---|---|---|---|
| new / old (diff) | 0.094827 / 0.018006 (0.076821) | 0.296820 / 0.000490 (0.296331) | 0.000212 / 0.000200 (0.000012) | 0.000046 / 0.000054 (-0.000008) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.022583 / 0.037411 (-0.014828) | 0.076318 / 0.014526 (0.061792) | 0.087435 / 0.176557 (-0.089121) | 0.127351 / 0.737135 (-0.609784) | 0.089051 / 0.296338 (-0.207287) |

### Benchmark: benchmark_iterating.json

| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.289476 / 0.215209 (0.074267) | 2.842065 / 2.077655 (0.764410) | 1.536857 / 1.504120 (0.032737) | 1.393914 / 1.541195 (-0.147281) | 1.392636 / 1.468490 (-0.075854) | 0.570299 / 4.584777 (-4.014478) | 0.982246 / 3.745712 (-2.763466) | 2.758773 / 5.269862 (-2.511088) | 1.728615 / 4.565676 (-2.837062) | 0.063944 / 0.424275 (-0.360331) | 0.005014 / 0.007607 (-0.002593) | 0.347474 / 0.226044 (0.121430) | 3.398092 / 2.268929 (1.129164) | 1.855134 / 55.444624 (-53.589491) | 1.568705 / 6.876477 (-5.307772) | 1.574201 / 2.142072 (-0.567871) | 0.649466 / 4.805227 (-4.155761) | 0.116330 / 6.500664 (-6.384334) | 0.040730 / 0.075469 (-0.034739) |

### Benchmark: benchmark_map_filter.json

| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |
|--------|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 1.000675 / 1.841788 (-0.841113) | 11.899660 / 8.074308 (3.825352) | 9.913335 / 10.191392 (-0.278058) | 0.132517 / 0.680424 (-0.547907) | 0.016467 / 0.534201 (-0.517734) | 0.282221 / 0.579283 (-0.297062) | 0.125205 / 0.434364 (-0.309159) | 0.374986 / 0.540337 (-0.165351) | 0.418666 / 1.386936 (-0.968270) |

</details>
</details>

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