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data/xnli_bn.tar.bz2

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+version https://git-lfs.github.com/spec/v1
+oid sha256:a91b4d3f8433a98fd6251396976b17b2385ef49ffbb207fabe8124fc6b066207
+size 21437836

xnli_bn.py

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+"""XNLI Bengali dataset"""
+import json
+import os
+import datasets
+_CITATION = """\
+@misc{bhattacharjee2021banglabert,
+      title={BanglaBERT: Combating Embedding Barrier in Multilingual Models for Low-Resource Language Understanding}, 
+      author={Abhik Bhattacharjee and Tahmid Hasan and Kazi Samin and Md Saiful Islam and M. Sohel Rahman and Anindya Iqbal and Rifat Shahriyar},
+      year={2021},
+      eprint={2101.00204},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+"""
+_DESCRIPTION = """\
+This is a Natural Language Inference (NLI) dataset for Bengali, curated using the subset of 
+MNLI data used in XNLI and state-of-the-art English to Bengali translation model. 
+"""
+_HOMEPAGE = "https://github.com/csebuetnlp/banglabert"
+_LICENSE = "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0)"
+_URL = "https://huggingface.co/datasets/csebuetnlp/xnli_bn/resolve/main/data/xnli_bn.tar.bz2"
+_VERSION = datasets.Version("0.0.1")
+
+class XnliBn(datasets.GeneratorBasedBuilder):
+    """XNLI Bengali dataset"""
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "sentence1": datasets.Value("string"),
+                "sentence2": datasets.Value("string"),
+                "label": datasets.features.ClassLabel(
+                    names=["contradiction", "entailment", "neurtral"]
+                ),
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+            version=_VERSION
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        data_dir = dl_manager.download_and_extract(_URL)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, "train.jsonl"),
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, "test.jsonl"),
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, "validation.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_, {
+                    "sentence1": data["sentence1"],
+                    "sentence2": data["sentence2"],
+                    "label": data["label"]
+                }