Title: Install transformers with numpy-2 CI
Author: albertvillanova (MEMBER)
State: closed
Created: 2024-08-21T11:14:59Z

Install transformers with numpy-2 CI.

Note that transformers no longer pins numpy < 2 since transformers-4.43.0:
- https://github.com/huggingface/transformers/pull/32018
- https://github.com/huggingface/transformers/releases/tag/v4.43.0

Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7119). 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) | 0.005156 / 0.011353 (-0.006197) | 0.003365 / 0.011008 (-0.007643) | 0.063451 / 0.038508 (0.024943) | 0.029510 / 0.023109 (0.006401) | 0.244825 / 0.275898 (-0.031074) | 0.265157 / 0.323480 (-0.058323) | 0.004239 / 0.007986 (-0.003747) | 0.002732 / 0.004328 (-0.001596) | 0.050412 / 0.004250 (0.046162) | 0.043608 / 0.037052 (0.006556) | 0.256635 / 0.258489 (-0.001854) | 0.277472 / 0.293841 (-0.016369) | 0.029329 / 0.128546 (-0.099217) | 0.012318 / 0.075646 (-0.063329) | 0.204751 / 0.419271 (-0.214520) | 0.036468 / 0.043533 (-0.007065) | 0.246773 / 0.255139 (-0.008366) | 0.263932 / 0.283200 (-0.019268) | 0.017053 / 0.141683 (-0.124629) | 1.173249 / 1.452155 (-0.278905) | 1.234186 / 1.492716 (-0.258531) |

### 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) | 0.092398 / 0.018006 (0.074391) | 0.309473 / 0.000490 (0.308983) | 0.000220 / 0.000200 (0.000020) | 0.000050 / 0.000054 (-0.000004) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.018553 / 0.037411 (-0.018858) | 0.062546 / 0.014526 (0.048020) | 0.073943 / 0.176557 (-0.102613) | 0.120498 / 0.737135 (-0.616638) | 0.075185 / 0.296338 (-0.221153) |

### 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) | 0.296899 / 0.215209 (0.081690) | 2.919088 / 2.077655 (0.841433) | 1.533146 / 1.504120 (0.029026) | 1.395441 / 1.541195 (-0.145754) | 1.399089 / 1.468490 (-0.069401) | 0.742750 / 4.584777 (-3.842027) | 2.390317 / 3.745712 (-1.355395) | 2.883166 / 5.269862 (-2.386695) | 1.854003 / 4.565676 (-2.711674) | 0.077140 / 0.424275 (-0.347136) | 0.005176 / 0.007607 (-0.002432) | 0.349391 / 0.226044 (0.123347) | 3.466043 / 2.268929 (1.197114) | 1.870619 / 55.444624 (-53.574005) | 1.559173 / 6.876477 (-5.317303) | 1.605480 / 2.142072 (-0.536592) | 0.786753 / 4.805227 (-4.018474) | 0.134869 / 6.500664 (-6.365795) | 0.042176 / 0.075469 (-0.033293) |

### 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) | 0.954256 / 1.841788 (-0.887532) | 11.194758 / 8.074308 (3.120449) | 9.129670 / 10.191392 (-1.061722) | 0.138318 / 0.680424 (-0.542106) | 0.014299 / 0.534201 (-0.519902) | 0.303704 / 0.579283 (-0.275579) | 0.262513 / 0.434364 (-0.171851) | 0.346539 / 0.540337 (-0.193798) | 0.429524 / 1.386936 (-0.957412) |

</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) | 0.005692 / 0.011353 (-0.005661) | 0.003423 / 0.011008 (-0.007586) | 0.050618 / 0.038508 (0.012110) | 0.031053 / 0.023109 (0.007944) | 0.275901 / 0.275898 (0.000003) | 0.294404 / 0.323480 (-0.029076) | 0.004303 / 0.007986 (-0.003682) | 0.002728 / 0.004328 (-0.001600) | 0.049757 / 0.004250 (0.045507) | 0.039997 / 0.037052 (0.002945) | 0.287291 / 0.258489 (0.028802) | 0.319186 / 0.293841 (0.025345) | 0.032558 / 0.128546 (-0.095988) | 0.012088 / 0.075646 (-0.063558) | 0.060746 / 0.419271 (-0.358525) | 0.034046 / 0.043533 (-0.009486) | 0.276170 / 0.255139 (0.021031) | 0.293673 / 0.283200 (0.010474) | 0.018018 / 0.141683 (-0.123665) | 1.158453 / 1.452155 (-0.293701) | 1.198599 / 1.492716 (-0.294118) |

### 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) | 0.093134 / 0.018006 (0.075127) | 0.304511 / 0.000490 (0.304021) | 0.000216 / 0.000200 (0.000016) | 0.000053 / 0.000054 (-0.000002) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.022991 / 0.037411 (-0.014421) | 0.077548 / 0.014526 (0.063022) | 0.087887 / 0.176557 (-0.088670) | 0.131786 / 0.737135 (-0.605349) | 0.088747 / 0.296338 (-0.207591) |

### 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) | 0.302811 / 0.215209 (0.087602) | 2.959276 / 2.077655 (0.881621) | 1.591348 / 1.504120 (0.087229) | 1.464731 / 1.541195 (-0.076464) | 1.474112 / 1.468490 (0.005622) | 0.741573 / 4.584777 (-3.843204) | 0.959229 / 3.745712 (-2.786483) | 2.895750 / 5.269862 (-2.374111) | 1.896051 / 4.565676 (-2.669625) | 0.079012 / 0.424275 (-0.345264) | 0.005494 / 0.007607 (-0.002113) | 0.355699 / 0.226044 (0.129655) | 3.524833 / 2.268929 (1.255905) | 1.972358 / 55.444624 (-53.472266) | 1.667249 / 6.876477 (-5.209228) | 1.658635 / 2.142072 (-0.483438) | 0.813184 / 4.805227 (-3.992044) | 0.134226 / 6.500664 (-6.366438) | 0.041087 / 0.075469 (-0.034382) |

### 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) | 1.038963 / 1.841788 (-0.802824) | 11.785835 / 8.074308 (3.711526) | 10.397027 / 10.191392 (0.205635) | 0.141748 / 0.680424 (-0.538676) | 0.014738 / 0.534201 (-0.519463) | 0.300056 / 0.579283 (-0.279227) | 0.127442 / 0.434364 (-0.306922) | 0.345013 / 0.540337 (-0.195324) | 0.449598 / 1.386936 (-0.937338) |

</details>
</details>

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