diff --git a/README.md b/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..b7fc2adab82764e2a6a7dd4ea28d61ccf8fe5109
--- /dev/null
+++ b/README.md
@@ -0,0 +1,258 @@
+---
+pretty_name: HALvest
+
+configs:
+- config_name: bg
+  data_files: "bg/*.gz"
+- config_name: br
+  data_files: "br/*.gz"
+- config_name: ca
+  data_files: "ca/*.gz"
+- config_name: cs
+  data_files: "cs/*.gz"
+- config_name: da
+  data_files: "da/*.gz"
+- config_name: de
+  data_files: "de/*.gz"
+- config_name: el
+  data_files: "el/*.gz"
+- config_name: en
+  data_files: "en/*.gz"
+- config_name: eo
+  data_files: "eo/*.gz"
+- config_name: es
+  data_files: "es/*.gz"
+- config_name: et
+  data_files: "et/*.gz"
+- config_name: eu
+  data_files: "eu/*.gz"
+- config_name: fa
+  data_files: "fa/*.gz"
+- config_name: fi
+  data_files: "fi/*.gz"
+- config_name: fr
+  data_files: "fr/*.gz"
+- config_name: gl
+  data_files: "gl/*.gz"
+- config_name: he
+  data_files: "he/*.gz"
+- config_name: hr
+  data_files: "hr/*.gz"
+- config_name: hu
+  data_files: "hu/*.gz"
+- config_name: hy
+  data_files: "hy/*.gz"
+- config_name: id
+  data_files: "id/*.gz"
+- config_name: it
+  data_files: "it/*.gz"
+- config_name: ko
+  data_files: "ko/*.gz"
+- config_name: "no"
+  data_files: "no/*.gz"
+- config_name: pl
+  data_files: "pl/*.gz"
+- config_name: pt
+  data_files: "pt/*.gz"
+- config_name: ro
+  data_files: "ro/*.gz"
+- config_name: ru
+  data_files: "ru/*.gz"
+- config_name: sk
+  data_files: "sk/*.gz"
+- config_name: sl
+  data_files: "sl/*.gz"
+- config_name: sv
+  data_files: "sv/*.gz"
+- config_name: sw
+  data_files: "sw/*.gz"
+- config_name: th
+  data_files: "th/*.gz"
+- config_name: tr
+  data_files: "tr/*.gz"
+
+language:
+- bg
+- br
+- ca
+- cs
+- da
+- de
+- el
+- en
+- eo
+- es
+- et
+- eu
+- fa
+- fi
+- fr
+- gl
+- he
+- hr
+- hu
+- hy
+- id
+- it
+- ko
+- "no"
+- pl
+- pt
+- ro
+- ru
+- sk
+- sl
+- sv
+- sw
+- th
+- tr
+
+size_categories:
+  - n<1K
+  - 1K<n<10K
+  - 10K<n<100K
+  - 100K<n<1M
+
+task_categories:
+- text-generation
+- fill-mask
+task_ids:
+- language-modeling
+- masked-language-modeling
+
+tags:
+- academia
+- research
+
+annotations_creators:
+- no-annotation
+
+multilinguality:
+- multilingual
+
+source_datasets:
+- HALvest-R
+---
+
+
+<div align="center">
+    <h1> HALvest </h1>
+    <h3> Open Scientific Papers Harvested from HAL </h3>
+</div>
+
+---
+
+
+## Dataset Description
+
+- **Repository:** [GitHub](https://github.com/Madjakul/HALvesting/tree/main)
+
+
+## Dataset Summary
+
+### overview:
+
+This dataset is comprised of fulltext from open papers found on [Hyper Articles en Ligne (HAL)](https://hal.science/). Our dump is mostly english/french but gather papers written in 34 languages across 13 domains.
+
+You can download the dataset using Hugging Face datasets:
+```py
+from datasets import load_dataset
+
+ds = load_dataset("Madjakul/HALvest", "en")
+```
+
+
+### Details
+
+Building the dataset is a four steps process: data fetching from HAL, data merging, data enriching and data filtering.
+
+1. We first request [HAL's API](https://api.archives-ouvertes.fr/docs) in order to gather open research papers and parse it -- effectively sorting papers by language. Then, we download the PDFs of the fetched data.
+2. Using [GROBID](https://github.com/kermitt2/grobid), we convert each PDF to an `xml-tei` format in order to have structured data. We convert each `xml-tei` file to a `txt` format before concatenating it with the paper's.
+3. We compute some statistics about each document.
+4. We filter the data based of off simple ratios to expurge badly encoded documents.
+
+
+### Languages
+
+ISO-639|Language|# Documents|# mT5 Tokens
+-------|--------|-----------|--------
+en|English|442,892|7,606,895,258
+fr|French|193,437|8,728,722,255
+es|Spanish|2,930|68,076,878
+it|Italian|1,172|48,747,986
+pt|Portuguese|934|32,918,832
+de|German|646|11,699,417
+ru|Russian|245|5,763,532
+eu|Basque|112|2,297,460
+pl|Polish|43|987,878
+el|Greek|42|1,680,696
+ro|Romanian|39|1,298,901
+ca|Catalan|28|975,078
+da|Danish|26|961,895
+br|Breton|24|998,088
+ko|Korean|17|226,268
+tr|Turkish|17|149,718
+hu|Hungarian|14|577,568
+eo|Esperanto|14|105,286
+fa|Persian|10|190,929
+hy|Armenian|10|127,988
+cs|Czech|9|712,263
+bg|Bulgarian|8|180,146
+id|Indonesian|9|53,075
+he|Hebrew|8|61,283
+hr|Croatian|8|40,621
+et|Estonian|7|20,405
+sv|Swedish|6|270,642
+no|Norwegian|6|62,767
+fi|Finnish|3|17,583
+sw|Swahili|2|73,921
+gl|Galician|2|29,688
+th|Thai|1|70,909
+sl|Slovenian|1|22,844
+sk|Slovak|1|12,997
+
+
+### Domains
+
+Domain|Code|# Documents|# mT5 Tokens
+------|----|-----------|------------
+Humanities and Social Sciences|shs|152,818|5,487,738,344
+Computer Science|info|143,229|2,436,890,715
+Life Sciences|sdv|111,038|3,008,633,879
+Engineering Sciences|spi|99,393|2,155,602,249
+Physics|phys|63,557|1,435,905,328
+Mathematics|math|54,393|1,359,277,656
+Chemical Science|chim|38,500|857,617,219
+Environmental Science|sde|30,827|566,560,266
+Sciences of the Universe|sdu|22,917|654,909,131
+Statistics|stat|20,571|1,449,842,318
+Cognitive science|scco|11,584|222,832,732
+Quantitative Finance|qfin|3,290|64,970,285
+Nonlinear Sciences|nlin|1,908|29,296,684
+
+You can browse through every domains and sub-domains here: https://hal.science/browse/domain.
+
+
+## Considerations for Using the Data
+
+The corpus is extracted from the [HAL's open archive](https://hal.science/) which distributes scientific publications following open access principles. The corpus is made up of both creative commons licensed and copyrighted documents (distribution authorized on HAL by the publisher). This must be considered prior to using this dataset for any purpose, other than training deep learning models, data mining etc. We do not own any of the text from which these data has been extracted.
+
+
+## Citation
+
+```bib
+@software{almanach_halvest_2024,
+  author = {Kulumba, Francis and Antoun, Wissam and Vimont, Guillaume and Romary, Laurent},
+  title = {HALvest: Open Scientific Papers Harvested from HAL.},
+  month = April,
+  year = 2024,
+  company = Almanach,
+  url = {https://github.com/Madjakul/HALvesting}
+}
+```
+
+
+## Dataset Copyright
+
+The licence terms for HALvest strictly follows the one from HAL. Please refer to the below license when using this dataset.
+- [HAL license](https://doc.archives-ouvertes.fr/en/legal-aspects/)
\ No newline at end of file
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diff --git a/halvest.py b/halvest.py
new file mode 100644
index 0000000000000000000000000000000000000000..18795d5aa3edd6282a7081b2b0e2df5e9307a938
--- /dev/null
+++ b/halvest.py
@@ -0,0 +1,168 @@
+# halvest.py
+
+import collections
+import gzip
+import json
+import os
+
+import datasets
+
+logger = datasets.logging.get_logger(__name__)
+
+_DESCRIPTION = "HALvest"
+_URL = "https://huggingface.co/datasets/Madjakul/HALvest"
+_LICENSE = """
+    The licence terms for HALvest strictly follows those of HAL.
+    Please refer to the below license when using this dataset.
+    - HAL license: https://doc.archives-ouvertes.fr/en/legal-aspects/
+    The corpus is extracted from the HAL's open archive which distributes scientific \
+    publications following open access principles. The corpus is made up of both \
+    creative commons licensed and copyrighted documents (distribution authorized on \
+    HAL by the publisher). This must be considered prior to using this dataset for any \
+    purpose, other than training deep learning models, data mining etc. We do not own \
+    any of the text from which these data has been extracted.
+"""
+_CITATION = """
+    @software{almanach_halvest_2024,
+    author = {Kulumba, Francis and Antoun, Wissam and Vimont, Guillaume and ROmary, Laurent},
+    title = {HALvest: Open Scientific Papers Harvested from HAL.},
+    month = {April},
+    year = {2024},
+    company = {Almanach},
+    url = {https://github.com/Madjakul/HALvesting}
+    }
+"""
+_BASE_DATA_PATH = "{language}/"
+_BASE_CHECKSUM_FILENAME = "checksum.sha256"
+
+
+def _languages():
+    """Creates the sorted dictionary of language codes, and language names."""
+    langs = {
+        "Armenian": "hy",
+        "Basque": "eu",
+        "Breton": "br",
+        "Bulgarian": "bg",
+        "Catalan": "ca",
+        "Croatian": "hr",
+        "Czech": "cs",
+        "Danish": "da",
+        "English": "en",
+        "Esperanto": "eo",
+        "Estonian": "et",
+        "Finnish": "fi",
+        "French": "fr",
+        "Galician": "gl",
+        "German": "de",
+        "Greek": "el",
+        "Hebrew": "he",
+        "Hungarian": "hu",
+        "Indonesian": "id",
+        "Italian": "it",
+        "Korean": "ko",
+        "Norwegian": "no",
+        "Persian": "fa",
+        "Polish": "pl",
+        "Portuguese": "pt",
+        "Romanian": "ro",
+        "Russian": "ru",
+        "Slovak": "sk",
+        "Slovenian": "sl",
+        "Spanish": "es",
+        "Swahili": "sw",
+        "Swedish": "sv",
+        "Thai": "th",
+        "Turkish": "tr",
+    }
+    langs = {v: k for k, v in langs.items()}
+    return collections.OrderedDict(sorted(langs.items()))
+
+
+class HALvestConfig(datasets.BuilderConfig):
+    """HALvest builder config.
+    Parameters
+    ----------
+    language: str
+        ISO 639 language code.
+    Attributes
+    ----------
+    base_data_path: str
+        f"{self.language}/".
+    """
+
+    def __init__(self, language: str, **kwargs):
+        if language not in _languages():
+            raise ValueError("Invalid language: %s " % language)
+
+        name = f"{language}"
+        description = f"""
+            {_languages()[language]} HALvest dataset from February 2024.
+        """
+        super(HALvestConfig, self).__init__(
+            name=name, description=description, **kwargs
+        )
+        self.language = language
+        self.base_data_path = _BASE_DATA_PATH.format(language=language)
+
+
+class HALvest(datasets.GeneratorBasedBuilder):
+    """HALvest: Open Scientific Papers Harvested from HAL."""
+
+    BUILDER_CONFIGS = [
+        HALvestConfig(language=language, version=datasets.Version("0.1.0"))
+        for language in _languages()
+    ]
+    BUILDER_CONFIG_CLASS = HALvestConfig
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "halid": datasets.Value("string"),
+                    "lang": datasets.Value("string"),
+                    "domain": datasets.Sequence("string"),
+                    "timestamp": datasets.Value("string"),
+                    "year": datasets.Value("string"),
+                    "url": datasets.Value("string"),
+                    "text": datasets.Value("string"),
+                }
+            ),
+            supervised_keys=None,
+            homepage=_URL,
+            citation=_CITATION,
+            license=_LICENSE,
+        )
+
+    def _split_generators(self, dl_manager):
+        checksum_path = os.path.join(
+            self.config.base_data_path, _BASE_CHECKSUM_FILENAME
+        )
+        checksum_file = dl_manager.download(checksum_path)
+
+        with open(checksum_file, encoding="utf-8") as f:
+            data_filenames = [line.split("\t")[1] for line in f if line]
+            data_urls = [
+                os.path.join(self.config.base_data_path, data_filename.rstrip("\n"))
+                for data_filename in data_filenames
+            ]
+
+        downloaded_files = dl_manager.download(
+            [url for url in data_urls if url.endswith(".gz")]
+        )
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN, gen_kwargs={"filepaths": downloaded_files}
+            )
+        ]
+
+    def _generate_examples(self, filepaths):
+        id_ = 0
+        for filepath in filepaths:
+            logger.info("Generating examples from = %s", filepath)
+            with gzip.open(open(filepath, "rb"), "rt", encoding="utf-8") as f:
+                for line in f:
+                    js_line = json.loads(line)
+                    yield id_, js_line
+                    id_ += 1
\ No newline at end of file
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