Support huggingface-hub pre-releases
State: closed | Author: albertvillanova (MEMBER)

Support `huggingface-hub` pre-releases.

This way we will have our CI green when testing `huggingface-hub` release candidates. See: https://github.com/huggingface/datasets/tree/ci-test-huggingface-hub-v0.20.0.rc1

Close #6513.

Comments: The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6516). 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) | 0.005309 / 0.011353 (-0.006044) | 0.003231 / 0.011008 (-0.007777) | 0.062690 / 0.038508 (0.024182) | 0.050811 / 0.023109 (0.027701) | 0.258319 / 0.275898 (-0.017579) | 0.275977 / 0.323480 (-0.047503) | 0.002842 / 0.007986 (-0.005143) | 0.002606 / 0.004328 (-0.001723) | 0.048672 / 0.004250 (0.044421) | 0.038730 / 0.037052 (0.001677) | 0.258531 / 0.258489 (0.000042) | 0.289327 / 0.293841 (-0.004514) | 0.027994 / 0.128546 (-0.100552) | 0.010446 / 0.075646 (-0.065200) | 0.207152 / 0.419271 (-0.212119) | 0.035839 / 0.043533 (-0.007693) | 0.258416 / 0.255139 (0.003277) | 0.274348 / 0.283200 (-0.008851) | 0.019661 / 0.141683 (-0.122022) | 1.103688 / 1.452155 (-0.348466) | 1.207711 / 1.492716 (-0.285006) |

### 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) | 0.090693 / 0.018006 (0.072687) | 0.300648 / 0.000490 (0.300158) | 0.000215 / 0.000200 (0.000015) | 0.000053 / 0.000054 (-0.000002) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.018589 / 0.037411 (-0.018822) | 0.061056 / 0.014526 (0.046530) | 0.074512 / 0.176557 (-0.102044) | 0.121260 / 0.737135 (-0.615875) | 0.073111 / 0.296338 (-0.223227) |

### 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) | 0.285811 / 0.215209 (0.070602) | 2.785081 / 2.077655 (0.707426) | 1.469493 / 1.504120 (-0.034627) | 1.346389 / 1.541195 (-0.194806) | 1.391866 / 1.468490 (-0.076624) | 0.567304 / 4.584777 (-4.017473) | 2.407150 / 3.745712 (-1.338562) | 2.809915 / 5.269862 (-2.459946) | 1.741185 / 4.565676 (-2.824491) | 0.063073 / 0.424275 (-0.361202) | 0.004974 / 0.007607 (-0.002633) | 0.336431 / 0.226044 (0.110386) | 3.331371 / 2.268929 (1.062443) | 1.841466 / 55.444624 (-53.603159) | 1.559065 / 6.876477 (-5.317411) | 1.585033 / 2.142072 (-0.557039) | 0.647469 / 4.805227 (-4.157759) | 0.117488 / 6.500664 (-6.383176) | 0.042535 / 0.075469 (-0.032934) |

### 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) | 0.936409 / 1.841788 (-0.905379) | 11.301514 / 8.074308 (3.227206) | 10.500465 / 10.191392 (0.309073) | 0.131316 / 0.680424 (-0.549107) | 0.014007 / 0.534201 (-0.520194) | 0.286932 / 0.579283 (-0.292351) | 0.263516 / 0.434364 (-0.170848) | 0.340883 / 0.540337 (-0.199454) | 0.443589 / 1.386936 (-0.943347) |

</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) | 0.005204 / 0.011353 (-0.006149) | 0.003472 / 0.011008 (-0.007536) | 0.049235 / 0.038508 (0.010727) | 0.050668 / 0.023109 (0.027559) | 0.270198 / 0.275898 (-0.005700) | 0.293942 / 0.323480 (-0.029538) | 0.003964 / 0.007986 (-0.004022) | 0.002596 / 0.004328 (-0.001733) | 0.048654 / 0.004250 (0.044404) | 0.039411 / 0.037052 (0.002358) | 0.271938 / 0.258489 (0.013449) | 0.304308 / 0.293841 (0.010467) | 0.029042 / 0.128546 (-0.099504) | 0.010414 / 0.075646 (-0.065232) | 0.058273 / 0.419271 (-0.360999) | 0.032507 / 0.043533 (-0.011025) | 0.271671 / 0.255139 (0.016532) | 0.289850 / 0.283200 (0.006650) | 0.017292 / 0.141683 (-0.124391) | 1.126160 / 1.452155 (-0.325995) | 1.177365 / 1.492716 (-0.315351) |

### 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) | 0.091158 / 0.018006 (0.073152) | 0.299143 / 0.000490 (0.298653) | 0.000217 / 0.000200 (0.000017) | 0.000042 / 0.000054 (-0.000012) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.022558 / 0.037411 (-0.014853) | 0.076139 / 0.014526 (0.061613) | 0.088344 / 0.176557 (-0.088212) | 0.126640 / 0.737135 (-0.610495) | 0.089736 / 0.296338 (-0.206602) |

### 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) | 0.295351 / 0.215209 (0.080142) | 2.895779 / 2.077655 (0.818125) | 1.585886 / 1.504120 (0.081766) | 1.458601 / 1.541195 (-0.082594) | 1.468880 / 1.468490 (0.000390) | 0.554686 / 4.584777 (-4.030091) | 2.466276 / 3.745712 (-1.279437) | 2.741938 / 5.269862 (-2.527924) | 1.711793 / 4.565676 (-2.853883) | 0.062928 / 0.424275 (-0.361347) | 0.005177 / 0.007607 (-0.002430) | 0.343908 / 0.226044 (0.117863) | 3.393360 / 2.268929 (1.124431) | 1.928800 / 55.444624 (-53.515824) | 1.652181 / 6.876477 (-5.224296) | 1.643667 / 2.142072 (-0.498405) | 0.632829 / 4.805227 (-4.172398) | 0.114583 / 6.500664 (-6.386081) | 0.041248 / 0.075469 (-0.034221) |

### 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) | 0.986196 / 1.841788 (-0.855592) | 12.006772 / 8.074308 (3.932464) | 10.522661 / 10.191392 (0.331269) | 0.133710 / 0.680424 (-0.546713) | 0.016714 / 0.534201 (-0.517487) | 0.286502 / 0.579283 (-0.292781) | 0.280090 / 0.434364 (-0.154273) | 0.326063 / 0.540337 (-0.214275) | 0.548485 / 1.386936 (-0.838452) |

</details>
</details>

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