added loading script and dataset card

README.md

@@ -0,0 +1,261 @@
+---
+annotations_creators:
+- other
+language_creators:
+- found
+language:
+- bg 
+- cs 
+- da 
+- de 
+- el 
+- en
+- es 
+- et 
+- fi 
+- fr 
+- ga
+- hu 
+- it 
+- lt 
+- lv 
+- mt
+- nl 
+- pl 
+- pt 
+- ro 
+- sk 
+- sl 
+- sv
+license:
+- cc-by-4.0
+multilinguality:
+- multilingual
+paperswithcode_id: null
+pretty_name: "MC4_Legal: A Corpus Covering the Legal Part of MC4 for European Languages"
+size_categories:
+- 10M<n<100M
+source_datasets:
+- original
+task_categories:
+- fill-mask
+
+---
+
+# Dataset Card for MC4_Legal: A Corpus Covering the Legal Part of MC4 for European Languages
+
+## Table of Contents
+
+- [Table of Contents](#table-of-contents)
+- [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+    - [Data Instances](#data-instances)
+    - [Data Fields](#data-fields)
+    - [Data Splits](#data-splits)
+- [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+    - [Annotations](#annotations)
+    - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+    - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Homepage:**
+- **Repository:** [GitHub](https://github.com/JoelNiklaus/LegalDatasets/tree/main/pretrain/mc4_legal)
+- **Paper:** 
+- **Leaderboard:**
+- **Point of Contact:** [Joel Niklaus](mailto:joel@niklaus.ai)
+
+### Dataset Summary
+
+This dataset contains large text resources (~106GB in total) from mc4 filtered for legal data that can be used for pretraining language models.
+
+This dataset uses a different filtering method compared to [mc4_legal](https://huggingface.co/datasets/joelito/mc4_legal) and uses the smaller filtered [c4](https://huggingface.co/datasets/c4) dataset for the English split to speed up the filtering.
+
+Use the dataset like this:
+```python
+from datasets import load_dataset
+dataset = load_dataset("joelito/mc4_legal", "de", split='train', streaming=True)
+```
+
+### Supported Tasks and Leaderboards
+
+The dataset supports the task of masked language modeling.
+
+### Languages
+
+The following languages are supported: bg, cs, da, de, el, en, es, et, fi, fr, ga, hu, it, lt, lv, mt, nl, pl, pt, ro, sk, sl, sv
+
+## Dataset Structure
+
+### Data Instances
+
+The file format is jsonl.xz and there is a validation and train split available.
+
+### Data Fields
+
+[More Information Needed]
+
+### Data Splits
+
+#### Data Size
+
+```bash
+$ xz --list data/*.xz
+Strms  Blocks   Compressed Uncompressed  Ratio  Check   Filename
+    1       1  2,080.7 KiB     33.4 MiB  0.061  CRC64   data/bg.train.0.jsonl.xz
+    1       1     22.8 KiB    315.9 KiB  0.072  CRC64   data/bg.validation.0.jsonl.xz
+    1       1    608.0 MiB  3,881.0 MiB  0.157  CRC64   data/cs.train.0.jsonl.xz
+    1       1    608.0 MiB  3,902.6 MiB  0.156  CRC64   data/cs.train.1.jsonl.xz
+    1       1    256.1 MiB  1,644.5 MiB  0.156  CRC64   data/cs.train.2.jsonl.xz
+    1       1  1,450.6 KiB  8,690.7 KiB  0.167  CRC64   data/cs.validation.0.jsonl.xz
+    1       1  7,578.6 KiB     38.3 MiB  0.193  CRC64   data/da.train.0.jsonl.xz
+    1       1     19.7 KiB     82.3 KiB  0.240  CRC64   data/da.validation.0.jsonl.xz
+    1       1    608.0 MiB  3,026.9 MiB  0.201  CRC64   data/de.train.0.jsonl.xz
+    1       1    608.0 MiB  3,038.7 MiB  0.200  CRC64   data/de.train.1.jsonl.xz
+    1       1    608.0 MiB  3,036.1 MiB  0.200  CRC64   data/de.train.2.jsonl.xz
+    1       1    608.0 MiB  3,040.3 MiB  0.200  CRC64   data/de.train.3.jsonl.xz
+    1       1    608.0 MiB  3,038.6 MiB  0.200  CRC64   data/de.train.4.jsonl.xz
+    1       1    608.0 MiB  3,044.2 MiB  0.200  CRC64   data/de.train.5.jsonl.xz
+    1       1    608.0 MiB  3,043.8 MiB  0.200  CRC64   data/de.train.6.jsonl.xz
+    1       1    608.0 MiB  3,038.2 MiB  0.200  CRC64   data/de.train.7.jsonl.xz
+    1       1     55.1 MiB    274.7 MiB  0.201  CRC64   data/de.train.8.jsonl.xz
+    1       1  5,033.5 KiB     24.5 MiB  0.201  CRC64   data/de.validation.0.jsonl.xz
+    1       1  1,280.9 KiB     17.0 MiB  0.073  CRC64   data/el.train.0.jsonl.xz
+    1       1      5,552 B     15.7 KiB  0.346  CRC64   data/el.validation.0.jsonl.xz
+    1       1    608.0 MiB  2,602.1 MiB  0.234  CRC64   data/en.train.0.jsonl.xz
+    1       1     90.0 MiB    386.5 MiB  0.233  CRC64   data/en.train.1.jsonl.xz
+    1       1    826.6 KiB  3,298.8 KiB  0.251  CRC64   data/en.validation.0.jsonl.xz
+    1       1    608.0 MiB  3,106.5 MiB  0.196  CRC64   data/es.train.0.jsonl.xz
+    1       1    608.0 MiB  3,118.1 MiB  0.195  CRC64   data/es.train.1.jsonl.xz
+    1       1    608.0 MiB  3,113.6 MiB  0.195  CRC64   data/es.train.2.jsonl.xz
+    1       1    608.0 MiB  3,122.5 MiB  0.195  CRC64   data/es.train.3.jsonl.xz
+    1       1    608.0 MiB  3,121.5 MiB  0.195  CRC64   data/es.train.4.jsonl.xz
+    1       1    608.0 MiB  3,122.9 MiB  0.195  CRC64   data/es.train.5.jsonl.xz
+    1       1    608.0 MiB  3,128.4 MiB  0.194  CRC64   data/es.train.6.jsonl.xz
+    1       1    608.0 MiB  3,129.5 MiB  0.194  CRC64   data/es.train.7.jsonl.xz
+    1       1    608.0 MiB  3,132.2 MiB  0.194  CRC64   data/es.train.8.jsonl.xz
+    1       1    528.5 MiB  2,722.5 MiB  0.194  CRC64   data/es.train.9.jsonl.xz
+    1       1  6,159.9 KiB     30.7 MiB  0.196  CRC64   data/es.validation.0.jsonl.xz
+    1       1     93.5 MiB    506.2 MiB  0.185  CRC64   data/et.train.0.jsonl.xz
+    1       1    136.2 KiB    571.3 KiB  0.238  CRC64   data/et.validation.0.jsonl.xz
+    1       1     60.6 MiB    312.6 MiB  0.194  CRC64   data/fi.train.0.jsonl.xz
+    1       1     63.2 KiB    262.4 KiB  0.241  CRC64   data/fi.validation.0.jsonl.xz
+    1       1    608.0 MiB  3,400.7 MiB  0.179  CRC64   data/fr.train.0.jsonl.xz
+    1       1    608.0 MiB  3,405.5 MiB  0.179  CRC64   data/fr.train.1.jsonl.xz
+    1       1    135.9 MiB    763.7 MiB  0.178  CRC64   data/fr.train.2.jsonl.xz
+    1       1  1,414.3 KiB  7,626.1 KiB  0.185  CRC64   data/fr.validation.0.jsonl.xz
+    1       1     31.2 KiB    146.4 KiB  0.213  CRC64   data/ga.train.0.jsonl.xz
+    1       0         32 B          0 B    ---  CRC64   data/ga.validation.0.jsonl.xz
+    1       1    211.5 MiB  1,407.3 MiB  0.150  CRC64   data/hu.train.0.jsonl.xz
+    1       1    212.9 KiB  1,287.6 KiB  0.165  CRC64   data/hu.validation.0.jsonl.xz
+    1       1    608.0 MiB  2,963.4 MiB  0.205  CRC64   data/it.train.0.jsonl.xz
+    1       1    608.0 MiB  2,970.0 MiB  0.205  CRC64   data/it.train.1.jsonl.xz
+    1       1    608.0 MiB  2,973.7 MiB  0.204  CRC64   data/it.train.2.jsonl.xz
+    1       1    315.2 MiB  1,541.6 MiB  0.204  CRC64   data/it.train.3.jsonl.xz
+    1       1  2,419.3 KiB     11.2 MiB  0.211  CRC64   data/it.validation.0.jsonl.xz
+    1       1  9,966.7 KiB     38.2 MiB  0.255  CRC64   data/lt.train.0.jsonl.xz
+    1       1     17.2 KiB     84.7 KiB  0.203  CRC64   data/lt.validation.0.jsonl.xz
+    1       1     66.4 KiB    326.7 KiB  0.203  CRC64   data/lv.train.0.jsonl.xz
+    1       0         32 B          0 B    ---  CRC64   data/lv.validation.0.jsonl.xz
+    1       1  2,851.6 KiB     16.7 MiB  0.167  CRC64   data/mt.train.0.jsonl.xz
+    1       1      2,092 B      5,079 B  0.412  CRC64   data/mt.validation.0.jsonl.xz
+    1       1     14.6 MiB     71.6 MiB  0.203  CRC64   data/nl.train.0.jsonl.xz
+    1       1     23.5 KiB     79.2 KiB  0.296  CRC64   data/nl.validation.0.jsonl.xz
+    1       1    608.0 MiB  3,635.5 MiB  0.167  CRC64   data/pl.train.0.jsonl.xz
+    1       1    608.0 MiB  3,646.0 MiB  0.167  CRC64   data/pl.train.1.jsonl.xz
+    1       1    401.9 MiB  2,409.0 MiB  0.167  CRC64   data/pl.train.2.jsonl.xz
+    1       1  1,870.5 KiB     10.5 MiB  0.173  CRC64   data/pl.validation.0.jsonl.xz
+    1       1    608.0 MiB  3,173.1 MiB  0.192  CRC64   data/pt.train.0.jsonl.xz
+    1       1    329.1 MiB  1,721.6 MiB  0.191  CRC64   data/pt.train.1.jsonl.xz
+    1       1    989.0 KiB  4,841.2 KiB  0.204  CRC64   data/pt.validation.0.jsonl.xz
+    1       1    365.2 MiB  2,237.9 MiB  0.163  CRC64   data/ro.train.0.jsonl.xz
+    1       1    419.2 KiB  2,320.4 KiB  0.181  CRC64   data/ro.validation.0.jsonl.xz
+    1       1    266.1 MiB  1,668.1 MiB  0.160  CRC64   data/sk.train.0.jsonl.xz
+    1       1    304.1 KiB  1,618.2 KiB  0.188  CRC64   data/sk.validation.0.jsonl.xz
+    1       1     81.6 MiB    416.1 MiB  0.196  CRC64   data/sl.train.0.jsonl.xz
+    1       1    101.0 KiB    416.6 KiB  0.242  CRC64   data/sl.validation.0.jsonl.xz
+    1       1    252.0 MiB  1,423.2 MiB  0.177  CRC64   data/sv.train.0.jsonl.xz
+    1       1    210.8 KiB  1,091.2 KiB  0.193  CRC64   data/sv.validation.0.jsonl.xz
+-------------------------------------------------------------------------------
+   74      72     20.0 GiB    106.2 GiB  0.189  CRC64   74 files
+```
+
+## Dataset Creation
+
+The dataset was created by filtering mc4 for legal data. 
+We used terms indicating legal citations to get the texts. 
+Note that this dataset can be quite noisy, and the quality is not known.
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+
+### 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
+
+Thanks to [@JoelNiklaus](https://github.com/joelniklaus) for adding this dataset.

legal-mc4.py

@@ -0,0 +1,133 @@
+"""Legal MC4"""
+import ast
+import json
+
+import datasets
+from huggingface_hub.file_download import hf_hub_url
+
+try:
+    import lzma as xz
+except ImportError:
+    import pylzma as xz
+
+datasets.logging.set_verbosity_info()
+logger = datasets.logging.get_logger(__name__)
+
+_DESCRIPTION = """
+Legal-MC4: A Corpus Covering the Legal Part of MC4 for European Languages
+"""
+
+_CITATION = """
+"""
+
+_REPO_ID = "joelito/legal-mc4"
+_URL = f"https://huggingface.co/datasets/{_REPO_ID}"
+
+_LANGUAGES = {
+    "bg": 0,
+    "cs": 2,
+    "da": 0,
+    "de": 8,
+    "el": 0,
+    "en": 1,
+    "es": 9,
+    "et": 1,
+    "fi": 0,
+    "fr": 2,
+    "ga": 0,
+    # "hr", # hr is not present in mc4
+    "hu": 0,
+    "it": 3,
+    "lt": 0,
+    "lv": 0,
+    "mt": 0,
+    "nl": 0,
+    "pl": 2,
+    "pt": 1,
+    "ro": 0,
+    "sk": 0,
+    "sl": 0,
+    "sv": 0,
+}
+_LANGS = list(_LANGUAGES.keys())
+
+
+class LegalMC4Config(datasets.BuilderConfig):
+    """BuilderConfig for Legal-MC4."""
+
+    def __init__(self, name: str, **kwargs):
+        """BuilderConfig for Legal-MC4.
+        Args:
+            name: One of bg,cs,da,de,el,en,es,et,fi,fr,ga,hu,it,lt,lv,mt,nl,pl,pt,ro,sk,sl,sv or all
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(LegalMC4Config, self).__init__(**kwargs)
+        self.name = name
+
+
+class MC4Legal(datasets.GeneratorBasedBuilder):
+    """Legal-MC4: A Corpus Covering the Legal Part of MC4 for European Languages"""
+
+    BUILDER_CONFIGS = [LegalMC4Config(language) for language in _LANGS + ["all"]]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "index": datasets.Value("int32"),
+                    "url": datasets.Value("string"),
+                    "timestamp": datasets.Value("timestamp[s]"),
+                    "matches": datasets.Sequence(datasets.Value("string")),
+                    "text": datasets.Value("string"),
+                }
+            ),
+            supervised_keys=None,
+            homepage=_URL,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        def get_url(file_name):
+            return hf_hub_url(repo_id=_REPO_ID, filename=f"data/{file_name}.jsonl.xz", repo_type="dataset")
+
+        data_urls = []
+        languages = _LANGS if self.config.name == "all" else [self.config.name]
+        split_generators = []
+        for split in [datasets.Split.TRAIN, datasets.Split.VALIDATION]:
+            for language in languages:
+                shards = range(_LANGUAGES[language] + 1) if split == datasets.Split.TRAIN else [0]
+                for shard in shards:
+                    data_urls.append(get_url(f"{language}.{str(split)}.{shard}"))
+
+            downloaded_files = dl_manager.download(data_urls)
+            split_generators.append(
+                datasets.SplitGenerator(name=split, gen_kwargs={"filepaths": downloaded_files})
+            )
+        return split_generators
+
+    def _generate_examples(self, filepaths):
+        """This function returns the examples in the raw (text) form by iterating on all the files."""
+        id_ = 0
+        for filepath in filepaths:
+            logger.info("Generating examples from = %s", filepath)
+            try:
+                with xz.open(open(filepath, "rb"), "rt", encoding="utf-8") as f:
+                    for line in f:
+                        if line:
+                            example = json.loads(line)
+                            if example is not None and isinstance(example, dict):
+                                timestamp = example.get("timestamp", "")
+                                # remove the Z at the end (time zone)
+                                if isinstance(timestamp, str) and timestamp.endswith("Z"):
+                                    timestamp = timestamp[:-1]
+                                yield id_, {
+                                    "index": example.get("index", ""),
+                                    "url": example.get("url", ""),
+                                    "timestamp": timestamp,
+                                    "matches": ast.literal_eval(example.get("matches", "")),
+                                    "text": example.get("text", ""),
+                                }
+                                id_ += 1
+            except Exception:
+                logger.exception("Error while processing file %s", filepath)