initial commit

README.md

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+---
+task_categories:
+  - text-generation
+language:
+  - en
+  - de
+  - fr
+  - es
+  - it
+pretty_name: Red Pajama V2 Data Foundation
+---
+
+### Getting Started
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("togethercomputer/RedPajama-Data-V2", name="en-head-middle-all") 
+```
+
+Or you can directly download the files using the following command:
+
+```bash
+wget 'https://data.together.xyz/redpajama-data-v2/v1.0.0/urls.txt'
+while read line; do
+    dload_loc=${line#https://data.together.xyz/redpajama-data-v2/v1.0.0/}
+    mkdir -p $(dirname $dload_loc)
+    wget "$line" -O "$dload_loc"
+done < urls.txt
+```
+
+After downloading the files, you can load the dataset from disk by setting the `RED_PAJAMA_DATA_DIR` environment
+variable XXXX TODO XXX
+
+A smaller sample of the dataset can be downloaded via
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("togethercomputer/RedPajama-Data-V2", name="en-sample")
+```
+
+A full set of scripts to recreate the dataset from can be
+found [here](https://github.com/togethercomputer/RedPajama-Data).
+
+### Dataset Summary
+
+TODO: Write a sentence about the dataset
+
+### Languages
+
+English, German, French, Italian, Spanish
+
+## Dataset Structure
+
+The dataset structure is as follows:
+
+```json
+{
+  TODO
+}
+```
+
+## Dataset Creation
+
+XXXX
+
+### Commoncrawl
+TODO
+
+To cite RedPajama, please use:
+
+```
+@software{together2023redpajama,
+  author = {Together Computer},
+  title = {RedPajama-Data-v2: a living data foundation for training open LLM models},
+  month = October,
+  year = 2023,
+  url = {https://github.com/togethercomputer/RedPajama-Data}
+}
+```
+
+### License
+
+TODO: double check this
+
+Please refer to the licenses of the data subsets you use.
+
+* [Common Crawl Foundation Terms of Use](https://commoncrawl.org/terms-of-use/full/)
+
+<!--
+### Annotations
+#### Annotation process
+[More Information Needed]
+#### Who are the annotators?
+[More Information Needed]
+### Personal and Sensitive Information
+[More Information Needed]
+## Considerations for Using the Data
+### Social Impact of Dataset
+[More Information Needed]
+### Discussion of Biases
+[More Information Needed]
+### Other Known Limitations
+[More Information Needed]
+## Additional Information
+### Dataset Curators
+[More Information Needed]
+### Licensing Information
+[More Information Needed]
+### Citation Information
+[More Information Needed]
+### Contributions
+[More Information Needed]
+-->

RedPajama-Data-V2.py

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+# Copyright 2023 Together Computer
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# Lint as: python3
+"""RedPajama V2: Quality annotated Web Text Documents."""
+
+import json
+
+import datasets
+import traceback
+import os
+import gzip
+
+logger = datasets.logging.get_logger(__name__)
+
+_DESCRIPTION = """\
+RedPajama V2 is a dataset of web documents and their quality signals.
+"""
+
+with open("_CC_SNAPSHOT_IDS", "r") as f:
+    _CC_SNAPSHOT_IDS = [line.strip() for line in f]
+
+with open("_QUALITY_SIGNAL_TAGS", "r") as f:
+    _QUALITY_SIGNAL_TAGS = [line.strip() for line in f]
+
+_URL_BASE = 'https://data.together.xyz/redpajama-data-v2/v1.0.0'
+_LANGUAGES = ("en", "de", "fr", "es", "it")
+_DATA_DIR = os.environ.get('RED_PAJAMA_V2_DATA_DIR', None)
+
+_LISTINGS_PATTERN = "urls/{language}-{snapshot}-{partition}.txt"
+
+
+class RedPajamaDataV2Config(datasets.BuilderConfig):
+    """BuilderConfig for RedPajama."""
+
+    def __init__(self, *args, language, partition, snapshots, **kwargs):
+        """BuilderConfig for RedPajama.
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(RedPajamaDataV2Config, self).__init__(**kwargs)
+        self.partition = partition
+        self.snapshots = snapshots
+        self.language = language
+
+
+_BUILDER_CONFIGS = []
+
+for lang in _LANGUAGES:
+    _BUILDER_CONFIGS.extend(
+        [
+            # single snapshot
+            RedPajamaDataV2Config(
+                name=f'{lang}-head-middle-{snapshot}',
+                partition='head-middle',
+                snapshots=[snapshot],
+                language=lang,
+                version=datasets.Version("1.0.0", ""),
+                description=f"RedPajamaV2 head-middle {lang}-{snapshot}",
+            )
+            for snapshot in _CC_SNAPSHOT_IDS
+        ] + [
+            # all snapshots
+            RedPajamaDataV2Config(
+                name=f'{lang}-head-middle-all',
+                partition='head_middle',
+                snapshots=_CC_SNAPSHOT_IDS,
+                language=lang,
+                version=datasets.Version("1.0.0", ""),
+                description=f"RedPajamaV2 head-middle {lang}"
+            )
+        ]
+    )
+
+    _BUILDER_CONFIGS.extend(
+        [
+            # single snapshot
+            RedPajamaDataV2Config(
+                name=f'{lang}-tail-{snapshot}',
+                partition='tail',
+                snapshots=[snapshot],
+                language=lang,
+                version=datasets.Version("1.0.0", ""),
+                description=f"RedPajamaV2 tail {lang}-{snapshot}",
+            )
+            for snapshot in _CC_SNAPSHOT_IDS
+        ] + [
+            # all snapshots
+            RedPajamaDataV2Config(
+                name=f'{lang}-tail-all',
+                partition='tail',
+                snapshots=_CC_SNAPSHOT_IDS,
+                language=lang,
+                version=datasets.Version("1.0.0", ""),
+                description=f"RedPajamaV2 tail {lang}"
+            )
+        ]
+    )
+
+
+class RedPajamaV2(datasets.GeneratorBasedBuilder):
+    """ RedPajama V2: Quality annotated Web Text Documents. """
+
+    BUILDER_CONFIGS = _BUILDER_CONFIGS
+
+    def _info(self):
+        if self.config.partition == "tail":
+            return datasets.DatasetInfo(
+                description=_DESCRIPTION,
+                features=datasets.Features(
+                    {
+                        "raw_content": datasets.Value("string"),
+                        "doc_id": datasets.Value("string"),
+                        "meta": datasets.Value("string"),
+                    }
+                ),
+                supervised_keys=None,
+            )
+        else:
+            return datasets.DatasetInfo(
+                description=_DESCRIPTION,
+                features=datasets.Features(
+                    {
+                        "raw_content": datasets.Value("string"),
+                        "doc_id": datasets.Value("string"),
+                        "meta": datasets.Value("string"),
+                        "quality_signals": datasets.Value("string")
+                    }
+                ),
+                supervised_keys=None,
+            )
+
+    def _split_generators(self, dl_manager):
+        url_lists = dl_manager.download_and_extract({
+            snapshot_id: _LISTINGS_PATTERN.format(
+                language=self.config.language,
+                snapshot=snapshot_id,
+                partition=self.config.partition,
+            )
+            for snapshot_id in self.config.snapshots
+        })
+
+        listings_ids = {}
+
+        for snapshot_id, listings_file in url_lists.items():
+            with open(listings_file, encoding="utf-8") as f:
+                listings_ids[snapshot_id] = [line.strip() for line in f]
+
+        # mapping document type -> url for download
+        if _DATA_DIR is not None:
+            documents_files = None
+            quality_signals_files = None
+        else:
+            # build urls pointing to documents
+            document_urls = {
+                snapshot_id: [
+                    os.path.join(_URL_BASE, f"documents/{lst_id}.json.gz")
+                    for lst_id in listings_ids[snapshot_id]
+                ]
+                for snapshot_id in self.config.snapshots
+            }
+
+            documents_files = dl_manager.download(document_urls)
+
+            # build urls pointing to quality signals
+            if self.config.partition == "head_middle":
+                quality_signals_urls = {
+                    snapshot_id: [
+                        os.path.join(
+                            _URL_BASE,
+                            f"quality_signals/{lst_id}.signals.json.gz"
+                        )
+                        for lst_id in listings_ids[snapshot_id]
+                    ]
+                    for snapshot_id in self.config.snapshots
+                }
+
+                quality_signals_files = dl_manager.download(
+                    quality_signals_urls
+                )
+            else:
+                quality_signals_files = {}
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "listings_ids": listings_ids,
+                    "documents_files": {
+                        snapshot_id: documents_files[snapshot_id]
+                        for snapshot_id in self.config.snapshots
+                    },
+                    "quality_signals_files": {
+                        snapshot_id: quality_signals_files.get(snapshot_id)
+                        for snapshot_id in self.config.snapshots
+                    }
+                }
+            )
+        ]
+
+    def _generate_examples(self, documents_files, quality_signals_files):
+        """ This function returns examples """
+        snapshots = list(documents_files.keys())
+
+        key = 0
+        for snapshot in snapshots:
+            docs_files = documents_files[snapshot]
+            if self.config.partition == "head_middle":
+                qs_files = quality_signals_files[snapshot]
+            else:
+                qs_files = None
+
+            assert len(docs_files) == len(qs_files)
+
+            for doc_file, qs_file in zip(docs_files, qs_files):
+                with gzip.open(doc_file, "rt", encoding="utf-8") as df:
+                    with gzip.open(qs_file, "rt", encoding="utf-8") as qf:
+                        for row, (doc, qs) in enumerate(zip(df, qf)):
+
+                            try:
+                                doc = json.loads(doc)
+                                qs = json.loads(qs)
+                                doc_id = qs["id"]
+
+                                meta = {
+                                    "url": doc["url"],
+                                    "source_domain": doc["source_domain"],
+                                    "date_download": doc["date_download"],
+                                    "digest": doc["digest"],
+                                }
+
+                                if self.config.partition == "tail":
+                                    yield key, {
+                                        "raw_content": doc["raw_content"],
+                                        "doc_id": doc_id,
+                                        "meta": json.dumps(meta),
+                                    }
+                                else:
+                                    yield key, {
+                                        "raw_content": doc["raw_content"],
+                                        "doc_id": doc_id,
+                                        "meta": json.dumps(meta),
+                                        "quality_signals": json.dumps(
+                                            qs["quality_signals"]
+                                        ),
+                                    }
+                                key += 1
+                            except Exception as e:
+                                print(f'doc_file: {doc_file}')
+                                print(f'qs_file: {qs_file}')
+                                print(f'row: {row}')
+                                traceback.print_exc()
+
+                                raise e

_CC_SNAPSHOT_IDS

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+2014-15
+2014-23
+2014-35
+2014-41
+2014-42
+2014-49
+2014-52
+2015-14
+2015-22
+2015-27
+2015-32
+2015-35
+2015-40
+2015-48
+2016-07
+2016-18
+2016-22
+2016-26
+2016-30
+2016-36
+2016-40
+2016-44
+2016-50
+2017-04
+2017-09
+2017-17
+2017-22
+2017-26
+2017-30
+2017-34
+2017-39
+2017-43
+2017-47
+2017-51
+2018-05
+2018-09
+2018-13
+2018-17
+2018-22
+2018-26
+2018-30
+2018-34
+2018-39
+2018-43
+2018-47
+2018-51
+2019-04
+2019-09
+2019-13
+2019-18
+2019-22
+2019-26
+2019-30
+2019-35
+2019-39
+2019-43
+2019-47
+2019-51
+2020-05
+2020-10
+2020-16
+2020-24
+2020-29
+2020-34
+2020-40
+2020-45
+2020-50
+2021-04
+2021-10
+2021-17
+2021-21
+2021-25
+2021-31
+2021-39
+2021-43
+2021-49
+2022-05
+2022-21
+2022-27
+2022-33
+2022-40
+2022-49
+2023-06
+2023-14

_QUALITY_SIGNAL_TAGS

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+ccnet_length
+ccnet_original_length
+ccnet_nlines
+ccnet_original_nlines
+ccnet_language_score
+ccnet_perplexity
+ccnet_bucket
+rps_doc_curly_bracket
+rps_doc_ldnoobw_words
+rps_doc_lorem_ipsum
+rps_doc_stop_word_fraction
+rps_doc_ut1_blacklist
+rps_doc_frac_all_caps_words
+rps_doc_frac_lines_end_with_ellipsis
+rps_doc_frac_no_alph_words
+rps_doc_frac_unique_words
+rps_doc_mean_word_length
+rps_doc_symbol_to_word_ratio
+rps_doc_unigram_entropy
+rps_doc_word_count
+rps_num_sentences
+rps_doc_frac_chars_dupe_10grams
+rps_doc_frac_chars_dupe_5grams
+rps_doc_frac_chars_dupe_6grams
+rps_doc_frac_chars_dupe_7grams
+rps_doc_frac_chars_dupe_8grams
+rps_doc_frac_chars_dupe_9grams
+rps_doc_frac_chars_top_2gram
+rps_doc_frac_chars_top_3gram
+rps_doc_frac_chars_top_4gram
+rps_lines_ending_with_terminal_punctution_mark
+rps_lines_javascript_counts
+rps_lines_num_words
+rps_lines_numerical_chars_fraction
+rps_lines_start_with_bulletpoint
+rps_lines_uppercase_letter_fraction
+rps_doc_ml_palm_score
+rps_doc_ml_wikipedia_score
+rps_doc_ml_wikiref_score
+rps_doc_books_importance
+rps_doc_openwebtext_importance
+rps_doc_wikipedia_importance