first version of mc4_legal dataset

.gitattributes

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README.md

@@ -0,0 +1,168 @@
+---
+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:** 
+- **Paper:** 
+- **Leaderboard:**
+- **Point of Contact:** [Joel Niklaus](mailto:joel.niklaus.2@bfh.ch)
+
+### Dataset Summary
+
+This dataset contains large text resources from mc4 filtered for legal data that can be used for pretraining language models.
+
+### Supported Tasks and Leaderboards
+
+The dataset supports the tasks 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 one split available ("train"). 
+
+### Data Fields
+
+[More Information Needed]
+
+### Data Splits
+
+[More Information Needed]
+
+## Dataset Creation
+
+### 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.

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mc4_legal.py

@@ -0,0 +1,119 @@
+"""MC4_Legal"""
+
+import json
+
+import datasets
+
+try:
+    import lzma as xz
+except ImportError:
+    import pylzma as xz
+
+datasets.logging.set_verbosity_info()
+logger = datasets.logging.get_logger(__name__)
+
+_DESCRIPTION = """
+"""
+
+_CITATION = """
+"""
+
+_URL = "https://huggingface.co/datasets/joelito/mc4_legal"
+_DATA_URL = f"{_URL}/resolve/main/data"
+
+_LANGUAGES = [
+    "bg",
+    "cs",
+    "da",
+    "de",
+    "el",
+    "en",
+    "es",
+    "et",
+    "fi",
+    "fr",
+    "ga",
+    # "hr", # hr is not present in mc4
+    "hu",
+    "it",
+    "lt",
+    "lv",
+    "mt",
+    "nl",
+    "pl",
+    "pt",
+    "ro",
+    "sk",
+    "sl",
+    "sv",
+]
+
+
+class MC4LegalConfig(datasets.BuilderConfig):
+    """BuilderConfig for MC4_Legal."""
+
+    def __init__(self, name: str, **kwargs):
+        """BuilderConfig for MC4_Legal.
+        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(MC4LegalConfig, self).__init__(**kwargs)
+        self.name = name
+
+
+class MC4Legal(datasets.GeneratorBasedBuilder):
+    """MC4_Legal: A Corpus Covering the Legal Part of MC4 for European Languages"""
+
+    BUILDER_CONFIGS = [MC4LegalConfig(language) for language in _LANGUAGES + ["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):
+        data_urls = []
+        languages = _LANGUAGES if self.config.language == "all" else [self.config.language]
+        for language in languages:
+            if language in ["de", "en", "es"]:  # here we need to chunk because the files are too large
+                data_urls.append([f"{_DATA_URL}/{language}_{idx}.jsonl.xz" for idx in [0, 1]])
+            else:
+                data_urls.append(f"{_DATA_URL}/{language}.jsonl.xz")
+
+        downloaded_files = dl_manager.download(data_urls)
+        return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": downloaded_files})]
+
+    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):
+                                yield id_, {
+                                    "index": example.get("index", ""),
+                                    "url": example.get("url", ""),
+                                    "timestamp": example.get("timestamp", ""),
+                                    "matches": example.get("matches", ""),
+                                    "text": example.get("text", ""),
+                                }
+                                id_ += 1
+            except:
+                print("Error reading file:", filepath)