Fix CI by temporarily pinning huggingface-hub < 0.23.0

As a hotfix for CI, temporarily pin `huggingface-hub` upper version

Fix #6860.

Revert once root cause is fixed, see:
- https://github.com/huggingface/transformers/issues/30618

The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6861). 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) | 0.005029 / 0.011353 (-0.006324) | 0.003217 / 0.011008 (-0.007791) | 0.062747 / 0.038508 (0.024239) | 0.030086 / 0.023109 (0.006976) | 0.251548 / 0.275898 (-0.024350) | 0.273215 / 0.323480 (-0.050265) | 0.003197 / 0.007986 (-0.004789) | 0.002706 / 0.004328 (-0.001623) | 0.049013 / 0.004250 (0.044763) | 0.044160 / 0.037052 (0.007107) | 0.266556 / 0.258489 (0.008067) | 0.291854 / 0.293841 (-0.001987) | 0.027463 / 0.128546 (-0.101083) | 0.010331 / 0.075646 (-0.065315) | 0.207195 / 0.419271 (-0.212077) | 0.035416 / 0.043533 (-0.008116) | 0.253180 / 0.255139 (-0.001959) | 0.274663 / 0.283200 (-0.008536) | 0.019132 / 0.141683 (-0.122551) | 1.174875 / 1.452155 (-0.277279) | 1.166828 / 1.492716 (-0.325888) |

### 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) | 0.092240 / 0.018006 (0.074234) | 0.299385 / 0.000490 (0.298895) | 0.000222 / 0.000200 (0.000022) | 0.000050 / 0.000054 (-0.000004) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.017994 / 0.037411 (-0.019417) | 0.066868 / 0.014526 (0.052342) | 0.074616 / 0.176557 (-0.101941) | 0.120632 / 0.737135 (-0.616503) | 0.074595 / 0.296338 (-0.221743) |

### 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) | 0.279008 / 0.215209 (0.063798) | 2.777927 / 2.077655 (0.700273) | 1.529495 / 1.504120 (0.025376) | 1.391528 / 1.541195 (-0.149666) | 1.420149 / 1.468490 (-0.048341) | 0.567526 / 4.584777 (-4.017251) | 2.400467 / 3.745712 (-1.345245) | 2.735778 / 5.269862 (-2.534083) | 1.718224 / 4.565676 (-2.847452) | 0.063009 / 0.424275 (-0.361266) | 0.005339 / 0.007607 (-0.002268) | 0.340130 / 0.226044 (0.114086) | 3.352796 / 2.268929 (1.083868) | 1.887427 / 55.444624 (-53.557198) | 1.598804 / 6.876477 (-5.277672) | 1.601566 / 2.142072 (-0.540506) | 0.640684 / 4.805227 (-4.164543) | 0.116694 / 6.500664 (-6.383970) | 0.041206 / 0.075469 (-0.034263) |

### 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) | 0.969163 / 1.841788 (-0.872625) | 11.475685 / 8.074308 (3.401377) | 9.397987 / 10.191392 (-0.793405) | 0.140131 / 0.680424 (-0.540293) | 0.014544 / 0.534201 (-0.519657) | 0.288122 / 0.579283 (-0.291161) | 0.262631 / 0.434364 (-0.171733) | 0.323565 / 0.540337 (-0.216773) | 0.421775 / 1.386936 (-0.965161) |

</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) | 0.005059 / 0.011353 (-0.006294) | 0.003185 / 0.011008 (-0.007824) | 0.050132 / 0.038508 (0.011624) | 0.030872 / 0.023109 (0.007763) | 0.257822 / 0.275898 (-0.018076) | 0.281645 / 0.323480 (-0.041835) | 0.004129 / 0.007986 (-0.003857) | 0.002703 / 0.004328 (-0.001625) | 0.049695 / 0.004250 (0.045445) | 0.040452 / 0.037052 (0.003400) | 0.278701 / 0.258489 (0.020212) | 0.297726 / 0.293841 (0.003885) | 0.028829 / 0.128546 (-0.099717) | 0.010011 / 0.075646 (-0.065636) | 0.058569 / 0.419271 (-0.360703) | 0.032564 / 0.043533 (-0.010969) | 0.259944 / 0.255139 (0.004805) | 0.279954 / 0.283200 (-0.003245) | 0.017804 / 0.141683 (-0.123879) | 1.147748 / 1.452155 (-0.304406) | 1.188390 / 1.492716 (-0.304327) |

### 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) | 0.091252 / 0.018006 (0.073246) | 0.308462 / 0.000490 (0.307972) | 0.000217 / 0.000200 (0.000017) | 0.000088 / 0.000054 (0.000033) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.022216 / 0.037411 (-0.015195) | 0.075547 / 0.014526 (0.061021) | 0.086085 / 0.176557 (-0.090471) | 0.128326 / 0.737135 (-0.608809) | 0.087253 / 0.296338 (-0.209085) |

### 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) | 0.301886 / 0.215209 (0.086677) | 2.940181 / 2.077655 (0.862527) | 1.663247 / 1.504120 (0.159127) | 1.545711 / 1.541195 (0.004517) | 1.542904 / 1.468490 (0.074414) | 0.556951 / 4.584777 (-4.027826) | 0.941925 / 3.745712 (-2.803788) | 2.740733 / 5.269862 (-2.529128) | 1.722801 / 4.565676 (-2.842875) | 0.060156 / 0.424275 (-0.364120) | 0.005008 / 0.007607 (-0.002599) | 0.348988 / 0.226044 (0.122944) | 3.454972 / 2.268929 (1.186044) | 2.015828 / 55.444624 (-53.428796) | 1.737828 / 6.876477 (-5.138649) | 1.747451 / 2.142072 (-0.394622) | 0.626865 / 4.805227 (-4.178362) | 0.114565 / 6.500664 (-6.386099) | 0.040562 / 0.075469 (-0.034907) |

### 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) | 0.997070 / 1.841788 (-0.844718) | 11.748577 / 8.074308 (3.674269) | 9.591721 / 10.191392 (-0.599671) | 0.131613 / 0.680424 (-0.548811) | 0.016560 / 0.534201 (-0.517641) | 0.288938 / 0.579283 (-0.290345) | 0.122196 / 0.434364 (-0.312168) | 0.380217 / 0.540337 (-0.160121) | 0.429886 / 1.386936 (-0.957050) |

</details>
</details>

![](https://cml.dev/watermark.png#7ae4314c34dae6a5339c11f7d1a2cbdfb76144d7 "CML watermark")