Fix decoding multi part extension
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The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6904). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.
2024-05-17T14:35:10Z
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takign the liberty to merge this for the viewer and a new dataset being released
2024-05-17T14:46:48Z
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<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) | 0.005004 / 0.011353 (-0.006349) | 0.003352 / 0.011008 (-0.007657) | 0.063035 / 0.038508 (0.024527) | 0.032031 / 0.023109 (0.008922) | 0.244801 / 0.275898 (-0.031097) | 0.270622 / 0.323480 (-0.052857) | 0.003110 / 0.007986 (-0.004876) | 0.002629 / 0.004328 (-0.001700) | 0.048784 / 0.004250 (0.044534) | 0.045779 / 0.037052 (0.008726) | 0.258642 / 0.258489 (0.000153) | 0.291606 / 0.293841 (-0.002235) | 0.028237 / 0.128546 (-0.100310) | 0.010184 / 0.075646 (-0.065463) | 0.202455 / 0.419271 (-0.216816) | 0.036012 / 0.043533 (-0.007521) | 0.248209 / 0.255139 (-0.006930) | 0.267315 / 0.283200 (-0.015884) | 0.019249 / 0.141683 (-0.122434) | 1.120420 / 1.452155 (-0.331735) | 1.169515 / 1.492716 (-0.323201) |

### 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) | 0.095193 / 0.018006 (0.077187) | 0.300544 / 0.000490 (0.300055) | 0.000214 / 0.000200 (0.000014) | 0.000050 / 0.000054 (-0.000004) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.019001 / 0.037411 (-0.018411) | 0.061857 / 0.014526 (0.047331) | 0.073379 / 0.176557 (-0.103178) | 0.121293 / 0.737135 (-0.615843) | 0.075665 / 0.296338 (-0.220673) |

### 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) | 0.285153 / 0.215209 (0.069944) | 2.875527 / 2.077655 (0.797873) | 1.479851 / 1.504120 (-0.024269) | 1.360691 / 1.541195 (-0.180504) | 1.385581 / 1.468490 (-0.082909) | 0.566312 / 4.584777 (-4.018465) | 2.400202 / 3.745712 (-1.345510) | 2.719241 / 5.269862 (-2.550620) | 1.706469 / 4.565676 (-2.859208) | 0.062129 / 0.424275 (-0.362146) | 0.005291 / 0.007607 (-0.002316) | 0.334585 / 0.226044 (0.108540) | 3.293347 / 2.268929 (1.024419) | 1.790490 / 55.444624 (-53.654134) | 1.505519 / 6.876477 (-5.370958) | 1.527730 / 2.142072 (-0.614343) | 0.644554 / 4.805227 (-4.160673) | 0.119775 / 6.500664 (-6.380889) | 0.056912 / 0.075469 (-0.018557) |

### 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) | 0.977512 / 1.841788 (-0.864275) | 11.293883 / 8.074308 (3.219575) | 9.669439 / 10.191392 (-0.521953) | 0.129910 / 0.680424 (-0.550514) | 0.014322 / 0.534201 (-0.519879) | 0.284967 / 0.579283 (-0.294316) | 0.265355 / 0.434364 (-0.169008) | 0.321965 / 0.540337 (-0.218372) | 0.415254 / 1.386936 (-0.971682) |

</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) | 0.005138 / 0.011353 (-0.006215) | 0.003321 / 0.011008 (-0.007687) | 0.049731 / 0.038508 (0.011223) | 0.032307 / 0.023109 (0.009198) | 0.266331 / 0.275898 (-0.009567) | 0.290863 / 0.323480 (-0.032617) | 0.004151 / 0.007986 (-0.003835) | 0.002684 / 0.004328 (-0.001644) | 0.048760 / 0.004250 (0.044510) | 0.042251 / 0.037052 (0.005199) | 0.280414 / 0.258489 (0.021925) | 0.305089 / 0.293841 (0.011248) | 0.029118 / 0.128546 (-0.099428) | 0.010276 / 0.075646 (-0.065370) | 0.057790 / 0.419271 (-0.361482) | 0.033290 / 0.043533 (-0.010243) | 0.267250 / 0.255139 (0.012111) | 0.285233 / 0.283200 (0.002034) | 0.018587 / 0.141683 (-0.123096) | 1.136198 / 1.452155 (-0.315957) | 1.185274 / 1.492716 (-0.307442) |

### 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) | 0.096355 / 0.018006 (0.078349) | 0.301827 / 0.000490 (0.301337) | 0.000216 / 0.000200 (0.000016) | 0.000052 / 0.000054 (-0.000003) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.022607 / 0.037411 (-0.014805) | 0.075724 / 0.014526 (0.061198) | 0.088197 / 0.176557 (-0.088359) | 0.127864 / 0.737135 (-0.609271) | 0.089294 / 0.296338 (-0.207044) |

### 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) | 0.289321 / 0.215209 (0.074112) | 2.832456 / 2.077655 (0.754802) | 1.559208 / 1.504120 (0.055088) | 1.426229 / 1.541195 (-0.114966) | 1.424564 / 1.468490 (-0.043926) | 0.557754 / 4.584777 (-4.027023) | 0.940179 / 3.745712 (-2.805533) | 2.713640 / 5.269862 (-2.556222) | 1.697583 / 4.565676 (-2.868093) | 0.062024 / 0.424275 (-0.362251) | 0.005270 / 0.007607 (-0.002337) | 0.339450 / 0.226044 (0.113406) | 3.333024 / 2.268929 (1.064096) | 1.946087 / 55.444624 (-53.498537) | 1.601057 / 6.876477 (-5.275420) | 1.599862 / 2.142072 (-0.542210) | 0.642838 / 4.805227 (-4.162390) | 0.120470 / 6.500664 (-6.380194) | 0.040815 / 0.075469 (-0.034654) |

### 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) | 1.012904 / 1.841788 (-0.828884) | 11.917035 / 8.074308 (3.842727) | 9.717822 / 10.191392 (-0.473570) | 0.141730 / 0.680424 (-0.538694) | 0.015750 / 0.534201 (-0.518451) | 0.284470 / 0.579283 (-0.294813) | 0.125662 / 0.434364 (-0.308702) | 0.380740 / 0.540337 (-0.159598) | 0.418119 / 1.386936 (-0.968817) |

</details>
</details>

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2024-05-17T14:52:55Z
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e.g. a field named `url.txt` should be a treated as text

I also included a small fix to support .npz correctly