Support commit_description parameter in push_to_hub

Support `commit_description` parameter in `push_to_hub`.

CC: @Wauplin 

The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6520). 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) | 0.005484 / 0.011353 (-0.005869) | 0.003537 / 0.011008 (-0.007471) | 0.062631 / 0.038508 (0.024123) | 0.048037 / 0.023109 (0.024927) | 0.240342 / 0.275898 (-0.035556) | 0.268103 / 0.323480 (-0.055377) | 0.002927 / 0.007986 (-0.005059) | 0.002609 / 0.004328 (-0.001719) | 0.048112 / 0.004250 (0.043862) | 0.046111 / 0.037052 (0.009058) | 0.249249 / 0.258489 (-0.009240) | 0.277723 / 0.293841 (-0.016118) | 0.028374 / 0.128546 (-0.100172) | 0.010900 / 0.075646 (-0.064746) | 0.206252 / 0.419271 (-0.213019) | 0.035262 / 0.043533 (-0.008271) | 0.247438 / 0.255139 (-0.007701) | 0.270003 / 0.283200 (-0.013197) | 0.019157 / 0.141683 (-0.122526) | 1.116833 / 1.452155 (-0.335322) | 1.174495 / 1.492716 (-0.318221) |

### 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) | 0.092490 / 0.018006 (0.074484) | 0.302794 / 0.000490 (0.302304) | 0.000213 / 0.000200 (0.000013) | 0.000043 / 0.000054 (-0.000011) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.018669 / 0.037411 (-0.018743) | 0.061902 / 0.014526 (0.047376) | 0.073612 / 0.176557 (-0.102945) | 0.121196 / 0.737135 (-0.615940) | 0.075960 / 0.296338 (-0.220378) |

### 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) | 0.286983 / 0.215209 (0.071774) | 2.836819 / 2.077655 (0.759165) | 1.506635 / 1.504120 (0.002515) | 1.387134 / 1.541195 (-0.154061) | 1.442310 / 1.468490 (-0.026180) | 0.571281 / 4.584777 (-4.013496) | 2.440220 / 3.745712 (-1.305492) | 2.775306 / 5.269862 (-2.494555) | 1.727047 / 4.565676 (-2.838630) | 0.064955 / 0.424275 (-0.359320) | 0.004982 / 0.007607 (-0.002625) | 0.343153 / 0.226044 (0.117108) | 3.388745 / 2.268929 (1.119817) | 1.878983 / 55.444624 (-53.565641) | 1.592642 / 6.876477 (-5.283835) | 1.601037 / 2.142072 (-0.541035) | 0.636882 / 4.805227 (-4.168345) | 0.117804 / 6.500664 (-6.382861) | 0.042467 / 0.075469 (-0.033002) |

### 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) | 0.941534 / 1.841788 (-0.900254) | 12.093230 / 8.074308 (4.018922) | 10.590854 / 10.191392 (0.399462) | 0.136636 / 0.680424 (-0.543788) | 0.015244 / 0.534201 (-0.518957) | 0.300216 / 0.579283 (-0.279067) | 0.267622 / 0.434364 (-0.166742) | 0.337526 / 0.540337 (-0.202811) | 0.426856 / 1.386936 (-0.960080) |

</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) | 0.005282 / 0.011353 (-0.006071) | 0.003595 / 0.011008 (-0.007413) | 0.049237 / 0.038508 (0.010729) | 0.054057 / 0.023109 (0.030948) | 0.269781 / 0.275898 (-0.006117) | 0.293544 / 0.323480 (-0.029936) | 0.003991 / 0.007986 (-0.003995) | 0.002705 / 0.004328 (-0.001623) | 0.048755 / 0.004250 (0.044505) | 0.040425 / 0.037052 (0.003373) | 0.264753 / 0.258489 (0.006264) | 0.312773 / 0.293841 (0.018932) | 0.030011 / 0.128546 (-0.098535) | 0.010707 / 0.075646 (-0.064939) | 0.058164 / 0.419271 (-0.361107) | 0.033365 / 0.043533 (-0.010168) | 0.268854 / 0.255139 (0.013715) | 0.283618 / 0.283200 (0.000418) | 0.019571 / 0.141683 (-0.122111) | 1.114738 / 1.452155 (-0.337417) | 1.178990 / 1.492716 (-0.313726) |

### 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) | 0.092183 / 0.018006 (0.074177) | 0.303797 / 0.000490 (0.303307) | 0.000218 / 0.000200 (0.000018) | 0.000052 / 0.000054 (-0.000003) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.023088 / 0.037411 (-0.014323) | 0.079813 / 0.014526 (0.065287) | 0.089593 / 0.176557 (-0.086964) | 0.128127 / 0.737135 (-0.609008) | 0.091578 / 0.296338 (-0.204761) |

### 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) | 0.300153 / 0.215209 (0.084944) | 2.919532 / 2.077655 (0.841877) | 1.587870 / 1.504120 (0.083750) | 1.459031 / 1.541195 (-0.082164) | 1.483305 / 1.468490 (0.014815) | 0.555865 / 4.584777 (-4.028912) | 2.388350 / 3.745712 (-1.357362) | 2.817947 / 5.269862 (-2.451914) | 1.764446 / 4.565676 (-2.801230) | 0.067142 / 0.424275 (-0.357133) | 0.005148 / 0.007607 (-0.002460) | 0.347998 / 0.226044 (0.121953) | 3.431208 / 2.268929 (1.162280) | 1.942175 / 55.444624 (-53.502450) | 1.676606 / 6.876477 (-5.199871) | 1.692431 / 2.142072 (-0.449641) | 0.645974 / 4.805227 (-4.159253) | 0.117729 / 6.500664 (-6.382935) | 0.041670 / 0.075469 (-0.033799) |

### 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) | 0.981554 / 1.841788 (-0.860234) | 12.671959 / 8.074308 (4.597650) | 11.230694 / 10.191392 (1.039302) | 0.132694 / 0.680424 (-0.547730) | 0.015694 / 0.534201 (-0.518507) | 0.290271 / 0.579283 (-0.289013) | 0.279358 / 0.434364 (-0.155006) | 0.326515 / 0.540337 (-0.213823) | 0.421755 / 1.386936 (-0.965181) |

</details>
</details>

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