Temporarily pin numpy<2.1 to fix CI

Temporarily pin numpy<2.1 to fix CI.

Fix #7111.

Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7114). 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) | 0.005381 / 0.011353 (-0.005972) | 0.003929 / 0.011008 (-0.007079) | 0.062505 / 0.038508 (0.023997) | 0.031048 / 0.023109 (0.007938) | 0.244794 / 0.275898 (-0.031104) | 0.270997 / 0.323480 (-0.052483) | 0.003186 / 0.007986 (-0.004799) | 0.002750 / 0.004328 (-0.001579) | 0.048289 / 0.004250 (0.044039) | 0.042617 / 0.037052 (0.005565) | 0.262607 / 0.258489 (0.004118) | 0.281778 / 0.293841 (-0.012063) | 0.029426 / 0.128546 (-0.099120) | 0.012466 / 0.075646 (-0.063181) | 0.205221 / 0.419271 (-0.214051) | 0.035535 / 0.043533 (-0.007998) | 0.247866 / 0.255139 (-0.007273) | 0.269121 / 0.283200 (-0.014079) | 0.018557 / 0.141683 (-0.123125) | 1.147982 / 1.452155 (-0.304173) | 1.188998 / 1.492716 (-0.303718) |

### 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) | 0.096550 / 0.018006 (0.078544) | 0.300497 / 0.000490 (0.300007) | 0.000219 / 0.000200 (0.000019) | 0.000043 / 0.000054 (-0.000011) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.019150 / 0.037411 (-0.018261) | 0.063518 / 0.014526 (0.048993) | 0.076643 / 0.176557 (-0.099914) | 0.122958 / 0.737135 (-0.614177) | 0.078511 / 0.296338 (-0.217828) |

### 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) | 0.278163 / 0.215209 (0.062953) | 2.733514 / 2.077655 (0.655859) | 1.434335 / 1.504120 (-0.069785) | 1.318976 / 1.541195 (-0.222219) | 1.352498 / 1.468490 (-0.115992) | 0.717326 / 4.584777 (-3.867450) | 2.403683 / 3.745712 (-1.342029) | 2.930366 / 5.269862 (-2.339495) | 1.879938 / 4.565676 (-2.685739) | 0.079016 / 0.424275 (-0.345259) | 0.005156 / 0.007607 (-0.002451) | 0.331099 / 0.226044 (0.105055) | 3.305878 / 2.268929 (1.036949) | 1.804185 / 55.444624 (-53.640439) | 1.508785 / 6.876477 (-5.367692) | 1.570102 / 2.142072 (-0.571970) | 0.796348 / 4.805227 (-4.008879) | 0.135737 / 6.500664 (-6.364927) | 0.042902 / 0.075469 (-0.032567) |

### 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) | 0.979923 / 1.841788 (-0.861865) | 11.656257 / 8.074308 (3.581949) | 9.745611 / 10.191392 (-0.445781) | 0.144497 / 0.680424 (-0.535927) | 0.022457 / 0.534201 (-0.511744) | 0.317251 / 0.579283 (-0.262032) | 0.264956 / 0.434364 (-0.169408) | 0.341873 / 0.540337 (-0.198464) | 0.439734 / 1.386936 (-0.947202) |

</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) | 0.006137 / 0.011353 (-0.005216) | 0.003999 / 0.011008 (-0.007009) | 0.049994 / 0.038508 (0.011486) | 0.032401 / 0.023109 (0.009292) | 0.272210 / 0.275898 (-0.003688) | 0.296038 / 0.323480 (-0.027442) | 0.004429 / 0.007986 (-0.003557) | 0.002894 / 0.004328 (-0.001434) | 0.049296 / 0.004250 (0.045045) | 0.041390 / 0.037052 (0.004337) | 0.288951 / 0.258489 (0.030462) | 0.321733 / 0.293841 (0.027892) | 0.033553 / 0.128546 (-0.094994) | 0.012122 / 0.075646 (-0.063524) | 0.060661 / 0.419271 (-0.358610) | 0.034752 / 0.043533 (-0.008781) | 0.272866 / 0.255139 (0.017727) | 0.292436 / 0.283200 (0.009237) | 0.018822 / 0.141683 (-0.122861) | 1.167758 / 1.452155 (-0.284397) | 1.207977 / 1.492716 (-0.284739) |

### 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) | 0.095862 / 0.018006 (0.077855) | 0.313746 / 0.000490 (0.313256) | 0.000219 / 0.000200 (0.000020) | 0.000056 / 0.000054 (0.000002) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.022940 / 0.037411 (-0.014472) | 0.076833 / 0.014526 (0.062307) | 0.088209 / 0.176557 (-0.088348) | 0.130154 / 0.737135 (-0.606981) | 0.089948 / 0.296338 (-0.206390) |

### 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) | 0.305393 / 0.215209 (0.090184) | 3.001629 / 2.077655 (0.923975) | 1.629378 / 1.504120 (0.125258) | 1.496022 / 1.541195 (-0.045173) | 1.542937 / 1.468490 (0.074447) | 0.734249 / 4.584777 (-3.850528) | 0.966226 / 3.745712 (-2.779486) | 3.051986 / 5.269862 (-2.217876) | 1.954694 / 4.565676 (-2.610982) | 0.081538 / 0.424275 (-0.342737) | 0.005198 / 0.007607 (-0.002409) | 0.355837 / 0.226044 (0.129793) | 3.537454 / 2.268929 (1.268525) | 2.036157 / 55.444624 (-53.408467) | 1.719255 / 6.876477 (-5.157222) | 1.744899 / 2.142072 (-0.397174) | 0.816034 / 4.805227 (-3.989193) | 0.135650 / 6.500664 (-6.365014) | 0.042206 / 0.075469 (-0.033263) |

### 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) | 1.055518 / 1.841788 (-0.786269) | 12.654622 / 8.074308 (4.580313) | 10.450807 / 10.191392 (0.259415) | 0.153567 / 0.680424 (-0.526857) | 0.016114 / 0.534201 (-0.518087) | 0.301182 / 0.579283 (-0.278101) | 0.130043 / 0.434364 (-0.304321) | 0.341289 / 0.540337 (-0.199048) | 0.434573 / 1.386936 (-0.952363) |

</details>
</details>

![](https://cml.dev/watermark.png#fb8ae4d2c3dda8c770fe48a40195775a7b517b6b "CML watermark")