Support push_to_hub without org/user to default to logged-in user

This behavior is aligned with:
- the behavior of `datasets` before merging #6519
  - the behavior described in the corresponding docstring
- the behavior of `huggingface_hub.create_repo`

Revert "Support push_to_hub canonical datasets (#6519)"
- This reverts commit a887ee78835573f5d80f9e414e8443b4caff3541.

Fix #6597.


The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6629). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

@huggingface/datasets, feel free to review this PR so that it can be included in the next release.

<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) | 0.005222 / 0.011353 (-0.006131) | 0.003621 / 0.011008 (-0.007387) | 0.063091 / 0.038508 (0.024583) | 0.029395 / 0.023109 (0.006285) | 0.231445 / 0.275898 (-0.044453) | 0.256716 / 0.323480 (-0.066764) | 0.004905 / 0.007986 (-0.003081) | 0.002703 / 0.004328 (-0.001625) | 0.048526 / 0.004250 (0.044276) | 0.041382 / 0.037052 (0.004330) | 0.247468 / 0.258489 (-0.011021) | 0.270670 / 0.293841 (-0.023171) | 0.028088 / 0.128546 (-0.100458) | 0.010661 / 0.075646 (-0.064985) | 0.205812 / 0.419271 (-0.213459) | 0.035880 / 0.043533 (-0.007653) | 0.237310 / 0.255139 (-0.017829) | 0.255440 / 0.283200 (-0.027760) | 0.018334 / 0.141683 (-0.123349) | 1.128815 / 1.452155 (-0.323340) | 1.204771 / 1.492716 (-0.287945) |

### 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) | 0.089175 / 0.018006 (0.071169) | 0.298584 / 0.000490 (0.298095) | 0.000206 / 0.000200 (0.000006) | 0.000043 / 0.000054 (-0.000012) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.018532 / 0.037411 (-0.018880) | 0.061158 / 0.014526 (0.046632) | 0.074177 / 0.176557 (-0.102380) | 0.119408 / 0.737135 (-0.617728) | 0.073821 / 0.296338 (-0.222518) |

### 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) | 0.277630 / 0.215209 (0.062420) | 2.735038 / 2.077655 (0.657383) | 1.437251 / 1.504120 (-0.066868) | 1.304596 / 1.541195 (-0.236598) | 1.316830 / 1.468490 (-0.151661) | 0.551057 / 4.584777 (-4.033720) | 2.337247 / 3.745712 (-1.408465) | 2.761501 / 5.269862 (-2.508361) | 1.729000 / 4.565676 (-2.836677) | 0.069398 / 0.424275 (-0.354877) | 0.005059 / 0.007607 (-0.002548) | 0.359594 / 0.226044 (0.133550) | 3.283325 / 2.268929 (1.014397) | 1.777410 / 55.444624 (-53.667214) | 1.518522 / 6.876477 (-5.357954) | 1.546712 / 2.142072 (-0.595361) | 0.627047 / 4.805227 (-4.178180) | 0.117058 / 6.500664 (-6.383606) | 0.043437 / 0.075469 (-0.032032) |

### 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) | 1.056303 / 1.841788 (-0.785484) | 11.552295 / 8.074308 (3.477987) | 10.184582 / 10.191392 (-0.006810) | 0.129061 / 0.680424 (-0.551363) | 0.014093 / 0.534201 (-0.520108) | 0.292268 / 0.579283 (-0.287015) | 0.264750 / 0.434364 (-0.169614) | 0.334770 / 0.540337 (-0.205567) | 0.436749 / 1.386936 (-0.950187) |

</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) | 0.005408 / 0.011353 (-0.005945) | 0.003650 / 0.011008 (-0.007358) | 0.054263 / 0.038508 (0.015755) | 0.031112 / 0.023109 (0.008003) | 0.270582 / 0.275898 (-0.005316) | 0.303506 / 0.323480 (-0.019974) | 0.004351 / 0.007986 (-0.003635) | 0.002654 / 0.004328 (-0.001674) | 0.049631 / 0.004250 (0.045381) | 0.045209 / 0.037052 (0.008156) | 0.284992 / 0.258489 (0.026503) | 0.316653 / 0.293841 (0.022812) | 0.049526 / 0.128546 (-0.079020) | 0.010696 / 0.075646 (-0.064951) | 0.057859 / 0.419271 (-0.361413) | 0.034227 / 0.043533 (-0.009306) | 0.269656 / 0.255139 (0.014517) | 0.288766 / 0.283200 (0.005567) | 0.017892 / 0.141683 (-0.123791) | 1.167492 / 1.452155 (-0.284662) | 1.217263 / 1.492716 (-0.275454) |

### 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) | 0.089306 / 0.018006 (0.071299) | 0.300774 / 0.000490 (0.300284) | 0.000198 / 0.000200 (-0.000002) | 0.000042 / 0.000054 (-0.000012) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.022050 / 0.037411 (-0.015361) | 0.076781 / 0.014526 (0.062255) | 0.086597 / 0.176557 (-0.089959) | 0.125094 / 0.737135 (-0.612042) | 0.089412 / 0.296338 (-0.206927) |

### 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) | 0.287444 / 0.215209 (0.072235) | 2.830047 / 2.077655 (0.752392) | 1.567492 / 1.504120 (0.063372) | 1.439875 / 1.541195 (-0.101320) | 1.461699 / 1.468490 (-0.006791) | 0.569595 / 4.584777 (-4.015182) | 2.454391 / 3.745712 (-1.291322) | 2.655829 / 5.269862 (-2.614032) | 1.756122 / 4.565676 (-2.809554) | 0.063333 / 0.424275 (-0.360942) | 0.005086 / 0.007607 (-0.002521) | 0.351210 / 0.226044 (0.125166) | 3.375545 / 2.268929 (1.106617) | 1.945367 / 55.444624 (-53.499258) | 1.662635 / 6.876477 (-5.213841) | 1.762859 / 2.142072 (-0.379213) | 0.651889 / 4.805227 (-4.153339) | 0.118341 / 6.500664 (-6.382323) | 0.040897 / 0.075469 (-0.034572) |

### 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) | 1.005270 / 1.841788 (-0.836518) | 12.247847 / 8.074308 (4.173539) | 10.828131 / 10.191392 (0.636739) | 0.129741 / 0.680424 (-0.550683) | 0.015184 / 0.534201 (-0.519017) | 0.295440 / 0.579283 (-0.283843) | 0.276759 / 0.434364 (-0.157605) | 0.329046 / 0.540337 (-0.211291) | 0.421750 / 1.386936 (-0.965186) |

</details>
</details>

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