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MorisienMT.py

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-import json
-import os
-
-import datasets
-
-_CITATION = """\
-Not Yet
-"""
-
-_DESCRIPTION = """\
-This is the MorisienMT dataset for Muritian Creole Machine translation, English-Creole and French-Creole machine translation to be specific. See readme/datacard for details.
-"""
-_HOMEPAGE = "https://huggingface.co/datasets/prajdabre/MorisienMT"
-
-_LICENSE = "Creative Commons Attribution-NonCommercial 4.0 International Public License"
-
-_URL = "https://huggingface.co/datasets/prajdabre/MorisienMT/resolve/main/data/{}.zip"
-
-
-_LANGUAGE_PAIRS = [
-    "en-cr",
-    "fr-cr",
-    "cr"
-]
-    
-
-class MorisienMT(datasets.GeneratorBasedBuilder):
-    VERSION = datasets.Version("1.0.0")
-    
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(
-            name="{}".format(lang),
-            version=datasets.Version("1.0.0")
-        )
-        for lang in _LANGUAGE_PAIRS
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "input": datasets.Value("string"),
-                    "target": datasets.Value("string"),
-                }
-            ),
-            supervised_keys=None,
-            homepage=_HOMEPAGE,
-            citation=_CITATION,
-            license=_LICENSE,
-            version=self.VERSION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        lang = str(self.config.name)
-        url = _URL.format(lang)
-
-        data_dir = dl_manager.download_and_extract(url)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, lang + "_train.jsonl"),
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, lang + "_test.jsonl"),
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, lang + "_dev.jsonl"),
-                },
-            ),
-        ]
-
-    def _generate_examples(self, filepath):
-        """Yields examples as (key, example) tuples."""
-        with open(filepath, encoding="utf-8") as f:
-            for idx_, row in enumerate(f):
-                data = json.loads(row)
-                yield idx_, {
-                    "input": data["input"],
-                    "target": data["target"],
-                    
-                }

README.md

@@ -1,28 +0,0 @@
----
-license: cc
----
-
-MorisienMT is a dataset for Mauritian Creole Machine Translation. 
-This dataset consists of training, development and test set splits for English--Creole as well as French--Creole translation.
-The data comes from a variety of sources and hence can be considered as belonging to the general domain.
-
-The development and test sets consist of 500 and 1000 sentences respectively. Both evaluation sets are trilingual.
-
-The training set for English--Creole contains 21,810 lines.
-The training set for French--Creole contains 15,239 lines.
-Additionally, one can extract a trilingual English-French-Creole training set of 13,861 lines using Creole as a pivot.
-
-Finally, we also provide a Creole monolingual corpus of 45,364 lines.
-
-Note that a significant portion of the dataset is a dictionary of word pairs/triplets, nevertheless it is a start.
-
-Usage: (TODO: beautify)
-1. Using huggingface datasets: load_dataset("prajdabre/MorisienMT", "en-cr", split="train")
-2. Convert to moses format: load the dataset as in step 1, each item is a json object so iterate over the loaded dataset object and use the key and value, "input" and "target" respectively, to get the translation pairs.
-
-Feel free to use the dataset for your research but don't forget to attribute our upcoming paper which will be uploaded to arxiv shortly.
-
-Note: MorisienMT was originally partly developed by Dr Aneerav Sukhoo from the University of Mauritius in 2014 when he was a visiting researcher in IIT Bombay. 
-Dr Sukhoo and I worked on the MT experiments together, but never publicly released the dataset back then. 
-Furthermore, the dataset splits and experiments were not done in a highly principled manner, which is required in the present day. 
-Therefore, we improve the quality of splits and officially release the data for people to use.

data/en-cr.zip → cr/morisien_mt-test.parquet

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data/fr-cr.zip → cr/morisien_mt-validation.parquet

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