Title: Remove underlines between badges
Author: andrewhong04 (CONTRIBUTOR)
State: closed
Created: 2024-06-12T14:32:11Z

## Before:
<img width="935" alt="image" src="https://github.com/huggingface/datasets/assets/35881688/93666e72-059b-4180-9e1d-ff176a3d9dac">

## After:
<img width="956" alt="image" src="https://github.com/huggingface/datasets/assets/35881688/75df7c3e-f473-44f0-a872-eeecf6a85fe2">

Comments:
<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) | 0.005326 / 0.011353 (-0.006027) | 0.003448 / 0.011008 (-0.007560) | 0.062516 / 0.038508 (0.024008) | 0.030222 / 0.023109 (0.007113) | 0.237006 / 0.275898 (-0.038892) | 0.258224 / 0.323480 (-0.065256) | 0.003191 / 0.007986 (-0.004795) | 0.002768 / 0.004328 (-0.001560) | 0.048754 / 0.004250 (0.044504) | 0.043694 / 0.037052 (0.006641) | 0.248832 / 0.258489 (-0.009657) | 0.272217 / 0.293841 (-0.021624) | 0.029684 / 0.128546 (-0.098862) | 0.011997 / 0.075646 (-0.063650) | 0.204047 / 0.419271 (-0.215225) | 0.035944 / 0.043533 (-0.007589) | 0.242094 / 0.255139 (-0.013045) | 0.258897 / 0.283200 (-0.024303) | 0.019228 / 0.141683 (-0.122455) | 1.110193 / 1.452155 (-0.341961) | 1.166780 / 1.492716 (-0.325937) |

### 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) | 0.097162 / 0.018006 (0.079156) | 0.303148 / 0.000490 (0.302659) | 0.000229 / 0.000200 (0.000029) | 0.000050 / 0.000054 (-0.000005) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.019981 / 0.037411 (-0.017431) | 0.062669 / 0.014526 (0.048144) | 0.074801 / 0.176557 (-0.101756) | 0.120509 / 0.737135 (-0.616626) | 0.075957 / 0.296338 (-0.220382) |

### 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) | 0.279527 / 0.215209 (0.064318) | 2.722749 / 2.077655 (0.645094) | 1.441770 / 1.504120 (-0.062350) | 1.312172 / 1.541195 (-0.229023) | 1.329418 / 1.468490 (-0.139072) | 0.723939 / 4.584777 (-3.860838) | 2.359146 / 3.745712 (-1.386566) | 2.963445 / 5.269862 (-2.306416) | 1.881974 / 4.565676 (-2.683702) | 0.078189 / 0.424275 (-0.346086) | 0.005249 / 0.007607 (-0.002358) | 0.334508 / 0.226044 (0.108463) | 3.271961 / 2.268929 (1.003032) | 1.817365 / 55.444624 (-53.627259) | 1.522755 / 6.876477 (-5.353721) | 1.514203 / 2.142072 (-0.627870) | 0.803486 / 4.805227 (-4.001741) | 0.134189 / 6.500664 (-6.366475) | 0.042761 / 0.075469 (-0.032708) |

### 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) | 0.971126 / 1.841788 (-0.870662) | 11.367159 / 8.074308 (3.292851) | 9.520174 / 10.191392 (-0.671218) | 0.142705 / 0.680424 (-0.537719) | 0.014586 / 0.534201 (-0.519615) | 0.300869 / 0.579283 (-0.278414) | 0.263161 / 0.434364 (-0.171203) | 0.336403 / 0.540337 (-0.203935) | 0.436088 / 1.386936 (-0.950848) |

</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) | 0.005800 / 0.011353 (-0.005553) | 0.003906 / 0.011008 (-0.007103) | 0.050197 / 0.038508 (0.011689) | 0.031348 / 0.023109 (0.008238) | 0.265636 / 0.275898 (-0.010262) | 0.286550 / 0.323480 (-0.036930) | 0.004502 / 0.007986 (-0.003484) | 0.002828 / 0.004328 (-0.001501) | 0.049668 / 0.004250 (0.045417) | 0.039552 / 0.037052 (0.002499) | 0.279091 / 0.258489 (0.020602) | 0.309987 / 0.293841 (0.016146) | 0.032104 / 0.128546 (-0.096442) | 0.011989 / 0.075646 (-0.063657) | 0.059875 / 0.419271 (-0.359397) | 0.033446 / 0.043533 (-0.010087) | 0.265256 / 0.255139 (0.010117) | 0.285649 / 0.283200 (0.002449) | 0.018330 / 0.141683 (-0.123353) | 1.140073 / 1.452155 (-0.312081) | 1.194538 / 1.492716 (-0.298178) |

### 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) | 0.093692 / 0.018006 (0.075685) | 0.301422 / 0.000490 (0.300932) | 0.000216 / 0.000200 (0.000016) | 0.000051 / 0.000054 (-0.000004) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.022844 / 0.037411 (-0.014568) | 0.077129 / 0.014526 (0.062603) | 0.087948 / 0.176557 (-0.088608) | 0.129905 / 0.737135 (-0.607230) | 0.089872 / 0.296338 (-0.206466) |

### 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) | 0.293135 / 0.215209 (0.077926) | 2.880280 / 2.077655 (0.802626) | 1.554250 / 1.504120 (0.050130) | 1.428005 / 1.541195 (-0.113190) | 1.520863 / 1.468490 (0.052373) | 0.759903 / 4.584777 (-3.824874) | 0.959674 / 3.745712 (-2.786038) | 2.848914 / 5.269862 (-2.420948) | 1.900355 / 4.565676 (-2.665322) | 0.079434 / 0.424275 (-0.344841) | 0.005487 / 0.007607 (-0.002121) | 0.344837 / 0.226044 (0.118793) | 3.401730 / 2.268929 (1.132802) | 1.887526 / 55.444624 (-53.557098) | 1.596821 / 6.876477 (-5.279655) | 1.732190 / 2.142072 (-0.409882) | 0.800929 / 4.805227 (-4.004299) | 0.132763 / 6.500664 (-6.367901) | 0.041185 / 0.075469 (-0.034284) |

### 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) | 0.994396 / 1.841788 (-0.847391) | 12.488692 / 8.074308 (4.414384) | 10.365952 / 10.191392 (0.174560) | 0.142951 / 0.680424 (-0.537472) | 0.015448 / 0.534201 (-0.518753) | 0.305577 / 0.579283 (-0.273706) | 0.126897 / 0.434364 (-0.307467) | 0.340784 / 0.540337 (-0.199554) | 0.461955 / 1.386936 (-0.924981) |

</details>
</details>

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