Issue: Update tqdm >= 4.66.3 to fix vulnerability
State: closed
Author: albertvillanova

Update tqdm >= 4.66.3 to fix vulnerability,

Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6870). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

<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) | 0.004997 / 0.011353 (-0.006356) | 0.003260 / 0.011008 (-0.007748) | 0.063342 / 0.038508 (0.024833) | 0.030399 / 0.023109 (0.007290) | 0.235665 / 0.275898 (-0.040233) | 0.256502 / 0.323480 (-0.066978) | 0.004113 / 0.007986 (-0.003873) | 0.002677 / 0.004328 (-0.001652) | 0.049614 / 0.004250 (0.045363) | 0.043075 / 0.037052 (0.006022) | 0.251788 / 0.258489 (-0.006701) | 0.280875 / 0.293841 (-0.012965) | 0.027479 / 0.128546 (-0.101067) | 0.010402 / 0.075646 (-0.065245) | 0.207296 / 0.419271 (-0.211975) | 0.035323 / 0.043533 (-0.008209) | 0.237719 / 0.255139 (-0.017420) | 0.259401 / 0.283200 (-0.023799) | 0.017574 / 0.141683 (-0.124109) | 1.109025 / 1.452155 (-0.343129) | 1.176264 / 1.492716 (-0.316452) |

### 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) | 0.098780 / 0.018006 (0.080774) | 0.304427 / 0.000490 (0.303937) | 0.000215 / 0.000200 (0.000016) | 0.000044 / 0.000054 (-0.000010) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.018189 / 0.037411 (-0.019222) | 0.061356 / 0.014526 (0.046830) | 0.073568 / 0.176557 (-0.102988) | 0.122412 / 0.737135 (-0.614723) | 0.074428 / 0.296338 (-0.221911) |

### 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) | 0.284719 / 0.215209 (0.069510) | 2.805719 / 2.077655 (0.728064) | 1.474386 / 1.504120 (-0.029734) | 1.341552 / 1.541195 (-0.199642) | 1.385354 / 1.468490 (-0.083136) | 0.575694 / 4.584777 (-4.009083) | 2.435102 / 3.745712 (-1.310610) | 2.822424 / 5.269862 (-2.447437) | 1.747609 / 4.565676 (-2.818068) | 0.064461 / 0.424275 (-0.359815) | 0.005370 / 0.007607 (-0.002237) | 0.341511 / 0.226044 (0.115467) | 3.384546 / 2.268929 (1.115617) | 1.846960 / 55.444624 (-53.597665) | 1.549294 / 6.876477 (-5.327183) | 1.562997 / 2.142072 (-0.579075) | 0.651108 / 4.805227 (-4.154120) | 0.118502 / 6.500664 (-6.382162) | 0.042356 / 0.075469 (-0.033113) |

### 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) | 1.015542 / 1.841788 (-0.826245) | 11.504899 / 8.074308 (3.430591) | 9.660870 / 10.191392 (-0.530522) | 0.145255 / 0.680424 (-0.535169) | 0.014602 / 0.534201 (-0.519599) | 0.286148 / 0.579283 (-0.293135) | 0.268358 / 0.434364 (-0.166006) | 0.323648 / 0.540337 (-0.216689) | 0.427384 / 1.386936 (-0.959552) |

</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) | 0.005671 / 0.011353 (-0.005681) | 0.004056 / 0.011008 (-0.006952) | 0.050673 / 0.038508 (0.012165) | 0.032334 / 0.023109 (0.009225) | 0.268541 / 0.275898 (-0.007357) | 0.294528 / 0.323480 (-0.028952) | 0.004592 / 0.007986 (-0.003393) | 0.002918 / 0.004328 (-0.001411) | 0.048857 / 0.004250 (0.044607) | 0.043072 / 0.037052 (0.006020) | 0.277031 / 0.258489 (0.018542) | 0.307189 / 0.293841 (0.013348) | 0.030500 / 0.128546 (-0.098046) | 0.010945 / 0.075646 (-0.064701) | 0.061067 / 0.419271 (-0.358204) | 0.060311 / 0.043533 (0.016778) | 0.268011 / 0.255139 (0.012872) | 0.290423 / 0.283200 (0.007224) | 0.019578 / 0.141683 (-0.122105) | 1.136353 / 1.452155 (-0.315802) | 1.196308 / 1.492716 (-0.296408) |

### 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) | 0.099429 / 0.018006 (0.081422) | 0.308350 / 0.000490 (0.307861) | 0.000221 / 0.000200 (0.000021) | 0.000045 / 0.000054 (-0.000010) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.022221 / 0.037411 (-0.015190) | 0.076744 / 0.014526 (0.062218) | 0.087768 / 0.176557 (-0.088788) | 0.129939 / 0.737135 (-0.607196) | 0.089763 / 0.296338 (-0.206576) |

### 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) | 0.299566 / 0.215209 (0.084357) | 2.916789 / 2.077655 (0.839134) | 1.555535 / 1.504120 (0.051415) | 1.432787 / 1.541195 (-0.108407) | 1.470983 / 1.468490 (0.002493) | 0.581468 / 4.584777 (-4.003309) | 0.993418 / 3.745712 (-2.752294) | 2.917487 / 5.269862 (-2.352374) | 1.799045 / 4.565676 (-2.766632) | 0.064520 / 0.424275 (-0.359755) | 0.005131 / 0.007607 (-0.002477) | 0.352277 / 0.226044 (0.126232) | 3.456564 / 2.268929 (1.187636) | 1.949195 / 55.444624 (-53.495430) | 1.627568 / 6.876477 (-5.248909) | 1.685246 / 2.142072 (-0.456826) | 0.653161 / 4.805227 (-4.152066) | 0.118308 / 6.500664 (-6.382356) | 0.042106 / 0.075469 (-0.033364) |

### 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) | 1.048028 / 1.841788 (-0.793759) | 12.425232 / 8.074308 (4.350924) | 10.127637 / 10.191392 (-0.063755) | 0.133095 / 0.680424 (-0.547329) | 0.015255 / 0.534201 (-0.518946) | 0.287927 / 0.579283 (-0.291357) | 0.129384 / 0.434364 (-0.304980) | 0.384828 / 0.540337 (-0.155510) | 0.427881 / 1.386936 (-0.959055) |

</details>
</details>

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