Delete loading script

wmt_14.py

@@ -1,77 +0,0 @@
-import datasets
-import os
-import json
-
-
-_CITATION = ""
-_DESCRIPTION = """
-    The 2014 Workshop on Statistical Machine Translation:
-    https://aclanthology.org/W14-3302.pdf
-
-    The scenario consists of 5 subsets, each of which is a parallel corpus between English and another language. The
-    non-English languages include Czech, German, French, Hindi, and Russian.
-
-    For each language pair, the validation and test set each includes around 3,000 examples, while the training set is
-    usually much larger. We therefore randomly downsample the training set to speedup data processing.
-
-    Task prompt structure:
-
-        Translate {source_language} to {target_language}:
-        {Hypothesis} = {Reference}
-
-    Example from WMT14 Fr-En:
-
-        Hypothesis: Assemblée générale
-        Reference: General Assembly
-"""
-
-class WMT14(datasets.GeneratorBasedBuilder):
-    VERSION = datasets.Version("1.0.0")
-
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name=name, version=datasets.Version("1.0.0"), description="")
-            for name in ["cs-en", "de-en", "fr-en", "hi-en", "ru-en"]
-        ]
-
-    def _info(self):
-        source_language, target_language = self.config.name.split('-')
-        features = datasets.Features(
-            {
-                source_language: datasets.Value("string"),
-                target_language: datasets.Value("string"),
-
-            }
-        )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            homepage="",
-            license="",
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        train_json = dl_manager.download(os.path.join(self.config.name, "train.jsonl"))
-        test_json = dl_manager.download(os.path.join(self.config.name, "test.jsonl"))
-        val_json = dl_manager.download(os.path.join(self.config.name, "validation.jsonl"))
-
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={"path": train_json},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={"path": test_json},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={"path": val_json},
-            )
-        ]
-
-    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
-    def _generate_examples(self, path):
-        with open(path, encoding="utf-8") as f:
-            for key, row in enumerate(f):
-                yield key, json.loads(row)