fix(ci): remove unnecessary permissions
Opened by McPatate (closed)

### What does this PR do?

Remove unnecessary permissions granted to the actions workflow.

Sorry for the mishap.

Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6962). 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) | 0.005520 / 0.011353 (-0.005833) | 0.003989 / 0.011008 (-0.007019) | 0.064786 / 0.038508 (0.026278) | 0.031075 / 0.023109 (0.007966) | 0.241619 / 0.275898 (-0.034279) | 0.275341 / 0.323480 (-0.048139) | 0.003139 / 0.007986 (-0.004847) | 0.002820 / 0.004328 (-0.001508) | 0.049766 / 0.004250 (0.045515) | 0.045047 / 0.037052 (0.007995) | 0.251906 / 0.258489 (-0.006583) | 0.285889 / 0.293841 (-0.007952) | 0.028297 / 0.128546 (-0.100249) | 0.010683 / 0.075646 (-0.064963) | 0.206467 / 0.419271 (-0.212805) | 0.036267 / 0.043533 (-0.007266) | 0.250720 / 0.255139 (-0.004419) | 0.268565 / 0.283200 (-0.014635) | 0.020394 / 0.141683 (-0.121289) | 1.114283 / 1.452155 (-0.337872) | 1.163884 / 1.492716 (-0.328833) |

### 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) | 0.112698 / 0.018006 (0.094692) | 0.302740 / 0.000490 (0.302251) | 0.000209 / 0.000200 (0.000009) | 0.000044 / 0.000054 (-0.000011) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.019337 / 0.037411 (-0.018075) | 0.062854 / 0.014526 (0.048328) | 0.077088 / 0.176557 (-0.099468) | 0.120926 / 0.737135 (-0.616209) | 0.075594 / 0.296338 (-0.220744) |

### 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) | 0.290787 / 0.215209 (0.075578) | 2.867894 / 2.077655 (0.790239) | 1.490043 / 1.504120 (-0.014076) | 1.356383 / 1.541195 (-0.184812) | 1.400229 / 1.468490 (-0.068261) | 0.582076 / 4.584777 (-4.002701) | 2.398270 / 3.745712 (-1.347442) | 2.856459 / 5.269862 (-2.413403) | 1.815545 / 4.565676 (-2.750131) | 0.063259 / 0.424275 (-0.361016) | 0.005056 / 0.007607 (-0.002551) | 0.347699 / 0.226044 (0.121655) | 3.466511 / 2.268929 (1.197582) | 1.862096 / 55.444624 (-53.582528) | 1.532324 / 6.876477 (-5.344152) | 1.599411 / 2.142072 (-0.542661) | 0.657350 / 4.805227 (-4.147878) | 0.118981 / 6.500664 (-6.381683) | 0.042224 / 0.075469 (-0.033245) |

### 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) | 0.965649 / 1.841788 (-0.876139) | 11.896501 / 8.074308 (3.822193) | 9.873923 / 10.191392 (-0.317469) | 0.141165 / 0.680424 (-0.539258) | 0.013885 / 0.534201 (-0.520316) | 0.291464 / 0.579283 (-0.287819) | 0.273153 / 0.434364 (-0.161211) | 0.324395 / 0.540337 (-0.215942) | 0.422040 / 1.386936 (-0.964897) |

</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) | 0.005640 / 0.011353 (-0.005713) | 0.004035 / 0.011008 (-0.006973) | 0.050831 / 0.038508 (0.012323) | 0.032841 / 0.023109 (0.009732) | 0.272226 / 0.275898 (-0.003672) | 0.297880 / 0.323480 (-0.025599) | 0.004397 / 0.007986 (-0.003588) | 0.002762 / 0.004328 (-0.001566) | 0.049887 / 0.004250 (0.045637) | 0.040372 / 0.037052 (0.003320) | 0.286337 / 0.258489 (0.027848) | 0.320015 / 0.293841 (0.026174) | 0.029992 / 0.128546 (-0.098554) | 0.010781 / 0.075646 (-0.064865) | 0.059391 / 0.419271 (-0.359880) | 0.034410 / 0.043533 (-0.009123) | 0.273024 / 0.255139 (0.017885) | 0.288953 / 0.283200 (0.005754) | 0.018072 / 0.141683 (-0.123611) | 1.125742 / 1.452155 (-0.326413) | 1.175233 / 1.492716 (-0.317483) |

### 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) | 0.093470 / 0.018006 (0.075463) | 0.313248 / 0.000490 (0.312758) | 0.000324 / 0.000200 (0.000124) | 0.000081 / 0.000054 (0.000026) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.023529 / 0.037411 (-0.013882) | 0.077305 / 0.014526 (0.062779) | 0.088916 / 0.176557 (-0.087640) | 0.128792 / 0.737135 (-0.608344) | 0.090141 / 0.296338 (-0.206197) |

### 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) | 0.291110 / 0.215209 (0.075901) | 2.848118 / 2.077655 (0.770464) | 1.581664 / 1.504120 (0.077544) | 1.446390 / 1.541195 (-0.094804) | 1.452594 / 1.468490 (-0.015896) | 0.571213 / 4.584777 (-4.013564) | 0.976382 / 3.745712 (-2.769330) | 2.756192 / 5.269862 (-2.513670) | 1.770274 / 4.565676 (-2.795403) | 0.064513 / 0.424275 (-0.359763) | 0.005334 / 0.007607 (-0.002273) | 0.347380 / 0.226044 (0.121335) | 3.424800 / 2.268929 (1.155871) | 1.942374 / 55.444624 (-53.502250) | 1.636069 / 6.876477 (-5.240407) | 1.795327 / 2.142072 (-0.346745) | 0.658942 / 4.805227 (-4.146285) | 0.119542 / 6.500664 (-6.381123) | 0.041826 / 0.075469 (-0.033643) |

### 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) | 1.007230 / 1.841788 (-0.834558) | 12.293084 / 8.074308 (4.218776) | 10.618104 / 10.191392 (0.426712) | 0.133691 / 0.680424 (-0.546733) | 0.015725 / 0.534201 (-0.518476) | 0.288860 / 0.579283 (-0.290423) | 0.130546 / 0.434364 (-0.303818) | 0.327279 / 0.540337 (-0.213059) | 0.428768 / 1.386936 (-0.958168) |

</details>
</details>

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