Fix link to quickstart docs in README.md


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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) | 0.006693 / 0.011353 (-0.004660) | 0.004331 / 0.011008 (-0.006677) | 0.098022 / 0.038508 (0.059514) | 0.032764 / 0.023109 (0.009654) | 0.295812 / 0.275898 (0.019914) | 0.325029 / 0.323480 (0.001550) | 0.005779 / 0.007986 (-0.002206) | 0.005381 / 0.004328 (0.001052) | 0.075785 / 0.004250 (0.071535) | 0.048759 / 0.037052 (0.011707) | 0.308986 / 0.258489 (0.050497) | 0.348000 / 0.293841 (0.054159) | 0.027686 / 0.128546 (-0.100860) | 0.008839 / 0.075646 (-0.066807) | 0.328389 / 0.419271 (-0.090883) | 0.062173 / 0.043533 (0.018640) | 0.312257 / 0.255139 (0.057119) | 0.325024 / 0.283200 (0.041824) | 0.103886 / 0.141683 (-0.037797) | 1.440215 / 1.452155 (-0.011940) | 1.528665 / 1.492716 (0.035948) |

### 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) | 0.210082 / 0.018006 (0.192076) | 0.442480 / 0.000490 (0.441990) | 0.006559 / 0.000200 (0.006359) | 0.000092 / 0.000054 (0.000038) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.026774 / 0.037411 (-0.010637) | 0.108362 / 0.014526 (0.093837) | 0.117631 / 0.176557 (-0.058926) | 0.176657 / 0.737135 (-0.560478) | 0.124154 / 0.296338 (-0.172184) |

### 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) | 0.428136 / 0.215209 (0.212927) | 4.270287 / 2.077655 (2.192632) | 2.014728 / 1.504120 (0.510608) | 1.806772 / 1.541195 (0.265577) | 1.946284 / 1.468490 (0.477794) | 0.525542 / 4.584777 (-4.059235) | 3.667025 / 3.745712 (-0.078687) | 1.878751 / 5.269862 (-3.391111) | 1.048321 / 4.565676 (-3.517356) | 0.065550 / 0.424275 (-0.358725) | 0.011881 / 0.007607 (0.004274) | 0.529873 / 0.226044 (0.303829) | 5.289641 / 2.268929 (3.020712) | 2.489403 / 55.444624 (-52.955221) | 2.141037 / 6.876477 (-4.735440) | 2.230735 / 2.142072 (0.088662) | 0.639781 / 4.805227 (-4.165447) | 0.141410 / 6.500664 (-6.359254) | 0.064374 / 0.075469 (-0.011095) |

### 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) | 1.159462 / 1.841788 (-0.682325) | 14.524730 / 8.074308 (6.450422) | 13.578070 / 10.191392 (3.386678) | 0.152138 / 0.680424 (-0.528286) | 0.017255 / 0.534201 (-0.516946) | 0.387607 / 0.579283 (-0.191676) | 0.413652 / 0.434364 (-0.020712) | 0.453644 / 0.540337 (-0.086693) | 0.550051 / 1.386936 (-0.836885) |

</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) | 0.006668 / 0.011353 (-0.004685) | 0.004677 / 0.011008 (-0.006331) | 0.075950 / 0.038508 (0.037442) | 0.032439 / 0.023109 (0.009329) | 0.381839 / 0.275898 (0.105941) | 0.419411 / 0.323480 (0.095931) | 0.005813 / 0.007986 (-0.002172) | 0.004090 / 0.004328 (-0.000238) | 0.075052 / 0.004250 (0.070802) | 0.048453 / 0.037052 (0.011401) | 0.388076 / 0.258489 (0.129587) | 0.431793 / 0.293841 (0.137952) | 0.028408 / 0.128546 (-0.100138) | 0.009028 / 0.075646 (-0.066618) | 0.082569 / 0.419271 (-0.336702) | 0.046772 / 0.043533 (0.003239) | 0.380182 / 0.255139 (0.125043) | 0.401828 / 0.283200 (0.118629) | 0.105388 / 0.141683 (-0.036294) | 1.453356 / 1.452155 (0.001201) | 1.561483 / 1.492716 (0.068767) |

### 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) | 0.008922 / 0.018006 (-0.009084) | 0.444112 / 0.000490 (0.443623) | 0.002756 / 0.000200 (0.002556) | 0.000104 / 0.000054 (0.000050) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.030408 / 0.037411 (-0.007003) | 0.112924 / 0.014526 (0.098399) | 0.124625 / 0.176557 (-0.051932) | 0.176915 / 0.737135 (-0.560220) | 0.129141 / 0.296338 (-0.167198) |

### 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) | 0.448197 / 0.215209 (0.232987) | 4.476548 / 2.077655 (2.398893) | 2.243977 / 1.504120 (0.739857) | 2.054060 / 1.541195 (0.512865) | 2.130680 / 1.468490 (0.662190) | 0.526815 / 4.584777 (-4.057962) | 3.759312 / 3.745712 (0.013600) | 3.333618 / 5.269862 (-1.936244) | 1.579611 / 4.565676 (-2.986065) | 0.065714 / 0.424275 (-0.358561) | 0.011939 / 0.007607 (0.004332) | 0.550313 / 0.226044 (0.324269) | 5.476946 / 2.268929 (3.208018) | 2.726521 / 55.444624 (-52.718104) | 2.364977 / 6.876477 (-4.511499) | 2.450624 / 2.142072 (0.308551) | 0.647174 / 4.805227 (-4.158053) | 0.141265 / 6.500664 (-6.359399) | 0.065493 / 0.075469 (-0.009976) |

### 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) | 1.249702 / 1.841788 (-0.592085) | 15.205647 / 8.074308 (7.131338) | 14.678310 / 10.191392 (4.486918) | 0.141539 / 0.680424 (-0.538884) | 0.017323 / 0.534201 (-0.516878) | 0.387602 / 0.579283 (-0.191681) | 0.415106 / 0.434364 (-0.019258) | 0.458146 / 0.540337 (-0.082192) | 0.553318 / 1.386936 (-0.833618) |

</details>
</details>

![](https://cml.dev/watermark.png#55127d7bf399fd2f3a8713db9822e8cb47cdbbed "CML watermark")


<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) | 0.008567 / 0.011353 (-0.002786) | 0.005245 / 0.011008 (-0.005763) | 0.115074 / 0.038508 (0.076566) | 0.032567 / 0.023109 (0.009458) | 0.352297 / 0.275898 (0.076399) | 0.393403 / 0.323480 (0.069923) | 0.006402 / 0.007986 (-0.001583) | 0.004353 / 0.004328 (0.000025) | 0.087903 / 0.004250 (0.083653) | 0.048424 / 0.037052 (0.011372) | 0.370078 / 0.258489 (0.111588) | 0.410192 / 0.293841 (0.116351) | 0.042396 / 0.128546 (-0.086150) | 0.014426 / 0.075646 (-0.061220) | 0.411358 / 0.419271 (-0.007914) | 0.059546 / 0.043533 (0.016013) | 0.364721 / 0.255139 (0.109582) | 0.385100 / 0.283200 (0.101901) | 0.100572 / 0.141683 (-0.041111) | 1.741457 / 1.452155 (0.289302) | 1.933134 / 1.492716 (0.440418) |

### 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) | 0.217177 / 0.018006 (0.199171) | 0.510399 / 0.000490 (0.509909) | 0.005542 / 0.000200 (0.005342) | 0.000120 / 0.000054 (0.000065) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.026852 / 0.037411 (-0.010559) | 0.125580 / 0.014526 (0.111054) | 0.132164 / 0.176557 (-0.044392) | 0.189073 / 0.737135 (-0.548063) | 0.135980 / 0.296338 (-0.160358) |

### 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) | 0.601924 / 0.215209 (0.386715) | 5.891397 / 2.077655 (3.813743) | 2.389494 / 1.504120 (0.885375) | 2.044013 / 1.541195 (0.502818) | 2.019367 / 1.468490 (0.550877) | 0.883807 / 4.584777 (-3.700970) | 5.141349 / 3.745712 (1.395636) | 2.607415 / 5.269862 (-2.662446) | 1.567268 / 4.565676 (-2.998409) | 0.102738 / 0.424275 (-0.321537) | 0.013480 / 0.007607 (0.005873) | 0.744979 / 0.226044 (0.518934) | 7.404182 / 2.268929 (5.135254) | 2.983406 / 55.444624 (-52.461219) | 2.331847 / 6.876477 (-4.544630) | 2.465119 / 2.142072 (0.323047) | 1.106725 / 4.805227 (-3.698502) | 0.205779 / 6.500664 (-6.294885) | 0.081019 / 0.075469 (0.005550) |

### 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) | 1.527840 / 1.841788 (-0.313947) | 16.989487 / 8.074308 (8.915179) | 18.016123 / 10.191392 (7.824731) | 0.216157 / 0.680424 (-0.464266) | 0.025393 / 0.534201 (-0.508808) | 0.496743 / 0.579283 (-0.082540) | 0.575365 / 0.434364 (0.141002) | 0.559978 / 0.540337 (0.019641) | 0.677474 / 1.386936 (-0.709462) |

</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) | 0.008913 / 0.011353 (-0.002440) | 0.005540 / 0.011008 (-0.005469) | 0.100001 / 0.038508 (0.061493) | 0.034432 / 0.023109 (0.011323) | 0.419824 / 0.275898 (0.143926) | 0.443566 / 0.323480 (0.120086) | 0.006372 / 0.007986 (-0.001614) | 0.004405 / 0.004328 (0.000077) | 0.094927 / 0.004250 (0.090677) | 0.050300 / 0.037052 (0.013248) | 0.424806 / 0.258489 (0.166317) | 0.480793 / 0.293841 (0.186952) | 0.050869 / 0.128546 (-0.077677) | 0.015899 / 0.075646 (-0.059747) | 0.111413 / 0.419271 (-0.307859) | 0.058093 / 0.043533 (0.014560) | 0.430575 / 0.255139 (0.175436) | 0.483786 / 0.283200 (0.200586) | 0.106878 / 0.141683 (-0.034805) | 1.763576 / 1.452155 (0.311422) | 1.837750 / 1.492716 (0.345033) |

### 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) | 0.011565 / 0.018006 (-0.006441) | 0.484411 / 0.000490 (0.483922) | 0.004869 / 0.000200 (0.004669) | 0.000111 / 0.000054 (0.000057) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.030706 / 0.037411 (-0.006706) | 0.126901 / 0.014526 (0.112375) | 0.130367 / 0.176557 (-0.046190) | 0.206568 / 0.737135 (-0.530567) | 0.146505 / 0.296338 (-0.149834) |

### 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) | 0.627266 / 0.215209 (0.412057) | 6.314049 / 2.077655 (4.236394) | 2.582920 / 1.504120 (1.078800) | 2.249401 / 1.541195 (0.708206) | 2.244960 / 1.468490 (0.776470) | 0.907770 / 4.584777 (-3.677007) | 5.349622 / 3.745712 (1.603910) | 4.591244 / 5.269862 (-0.678618) | 2.301612 / 4.565676 (-2.264064) | 0.108813 / 0.424275 (-0.315462) | 0.013187 / 0.007607 (0.005580) | 0.806071 / 0.226044 (0.580027) | 7.843903 / 2.268929 (5.574974) | 3.405968 / 55.444624 (-52.038656) | 2.564301 / 6.876477 (-4.312176) | 2.652208 / 2.142072 (0.510135) | 1.168142 / 4.805227 (-3.637086) | 0.218551 / 6.500664 (-6.282113) | 0.078120 / 0.075469 (0.002651) |

### 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) | 1.562517 / 1.841788 (-0.279271) | 17.519325 / 8.074308 (9.445017) | 20.727083 / 10.191392 (10.535691) | 0.207135 / 0.680424 (-0.473288) | 0.028208 / 0.534201 (-0.505993) | 0.496157 / 0.579283 (-0.083126) | 0.569239 / 0.434364 (0.134875) | 0.566137 / 0.540337 (0.025799) | 0.704208 / 1.386936 (-0.682728) |

</details>
</details>

![](https://cml.dev/watermark.png#8eb3f34d876da98e722d866be90d7f26135ea9e3 "CML watermark")