Remove instructions for `ffmpeg` system package installation on Colab
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<summary>Show benchmarks</summary>

PyArrow==6.0.0

<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) | 0.014525 / 0.011353 (0.003172) | 0.006871 / 0.011008 (-0.004137) | 0.135577 / 0.038508 (0.097069) | 0.039620 / 0.023109 (0.016511) | 0.499829 / 0.275898 (0.223931) | 0.571000 / 0.323480 (0.247520) | 0.009726 / 0.007986 (0.001740) | 0.005654 / 0.004328 (0.001325) | 0.104732 / 0.004250 (0.100482) | 0.046849 / 0.037052 (0.009796) | 0.486667 / 0.258489 (0.228178) | 0.543611 / 0.293841 (0.249770) | 0.056414 / 0.128546 (-0.072133) | 0.019974 / 0.075646 (-0.055672) | 0.484878 / 0.419271 (0.065606) | 0.059244 / 0.043533 (0.015711) | 0.490046 / 0.255139 (0.234907) | 0.517427 / 0.283200 (0.234227) | 0.114692 / 0.141683 (-0.026991) | 1.935935 / 1.452155 (0.483780) | 1.990253 / 1.492716 (0.497537) |

### 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) | 0.271008 / 0.018006 (0.253002) | 0.610964 / 0.000490 (0.610474) | 0.013423 / 0.000200 (0.013223) | 0.000523 / 0.000054 (0.000468) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.031940 / 0.037411 (-0.005472) | 0.130755 / 0.014526 (0.116229) | 0.146616 / 0.176557 (-0.029941) | 0.239386 / 0.737135 (-0.497749) | 0.146612 / 0.296338 (-0.149726) |

### 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) | 0.675383 / 0.215209 (0.460174) | 6.656828 / 2.077655 (4.579174) | 2.741231 / 1.504120 (1.237111) | 2.232921 / 1.541195 (0.691726) | 2.172116 / 1.468490 (0.703626) | 1.221623 / 4.584777 (-3.363154) | 5.683653 / 3.745712 (1.937941) | 5.344137 / 5.269862 (0.074275) | 2.969670 / 4.565676 (-1.596006) | 0.142107 / 0.424275 (-0.282168) | 0.015808 / 0.007607 (0.008201) | 0.767366 / 0.226044 (0.541321) | 8.059605 / 2.268929 (5.790676) | 3.333535 / 55.444624 (-52.111089) | 2.669619 / 6.876477 (-4.206857) | 2.652989 / 2.142072 (0.510917) | 1.526397 / 4.805227 (-3.278830) | 0.265609 / 6.500664 (-6.235055) | 0.082759 / 0.075469 (0.007290) |

### 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) | 1.631086 / 1.841788 (-0.210701) | 18.701351 / 8.074308 (10.627043) | 22.843802 / 10.191392 (12.652410) | 0.240134 / 0.680424 (-0.440290) | 0.046683 / 0.534201 (-0.487518) | 0.576488 / 0.579283 (-0.002795) | 0.650123 / 0.434364 (0.215759) | 0.661190 / 0.540337 (0.120853) | 0.759563 / 1.386936 (-0.627373) |

</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) | 0.009883 / 0.011353 (-0.001470) | 0.006692 / 0.011008 (-0.004316) | 0.098550 / 0.038508 (0.060042) | 0.035188 / 0.023109 (0.012078) | 0.463535 / 0.275898 (0.187637) | 0.472762 / 0.323480 (0.149282) | 0.007199 / 0.007986 (-0.000787) | 0.007961 / 0.004328 (0.003632) | 0.093140 / 0.004250 (0.088890) | 0.051752 / 0.037052 (0.014700) | 0.453412 / 0.258489 (0.194922) | 0.502741 / 0.293841 (0.208900) | 0.056006 / 0.128546 (-0.072540) | 0.020164 / 0.075646 (-0.055482) | 0.116828 / 0.419271 (-0.302444) | 0.067205 / 0.043533 (0.023672) | 0.442715 / 0.255139 (0.187576) | 0.472525 / 0.283200 (0.189326) | 0.122767 / 0.141683 (-0.018915) | 1.881366 / 1.452155 (0.429212) | 1.978786 / 1.492716 (0.486069) |

### 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) | 0.284180 / 0.018006 (0.266174) | 0.601556 / 0.000490 (0.601067) | 0.008455 / 0.000200 (0.008255) | 0.000112 / 0.000054 (0.000057) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.033515 / 0.037411 (-0.003896) | 0.136407 / 0.014526 (0.121881) | 0.143341 / 0.176557 (-0.033215) | 0.225394 / 0.737135 (-0.511741) | 0.153343 / 0.296338 (-0.142995) |

### 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) | 0.688202 / 0.215209 (0.472993) | 6.576502 / 2.077655 (4.498847) | 2.839175 / 1.504120 (1.335055) | 2.481152 / 1.541195 (0.939957) | 2.617227 / 1.468490 (1.148736) | 1.314854 / 4.584777 (-3.269922) | 5.805950 / 3.745712 (2.060238) | 3.188930 / 5.269862 (-2.080932) | 2.141719 / 4.565676 (-2.423957) | 0.145069 / 0.424275 (-0.279206) | 0.014567 / 0.007607 (0.006960) | 0.780000 / 0.226044 (0.553955) | 7.898016 / 2.268929 (5.629088) | 3.549060 / 55.444624 (-51.895564) | 2.856569 / 6.876477 (-4.019907) | 3.117719 / 2.142072 (0.975647) | 1.512560 / 4.805227 (-3.292668) | 0.262689 / 6.500664 (-6.237975) | 0.085979 / 0.075469 (0.010509) |

### 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) | 1.623550 / 1.841788 (-0.218238) | 19.597063 / 8.074308 (11.522755) | 21.293369 / 10.191392 (11.101977) | 0.263780 / 0.680424 (-0.416643) | 0.027289 / 0.534201 (-0.506912) | 0.560361 / 0.579283 (-0.018922) | 0.646288 / 0.434364 (0.211924) | 0.712699 / 0.540337 (0.172361) | 0.818332 / 1.386936 (-0.568604) |

</details>
</details>

![](https://cml.dev/watermark.png#b304de5dde30c945ec1397d3b4fe86f3b323ca8b "CML watermark")

Colab now has Ubuntu 20.04 which already has `ffmpeg` of required (>4) version. 