dummy

README.md

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+---
+license: cc-by-nc-2.0
+dataset_info:
+  config_name: mydata
+  features:
+  - name: id
+    dtype: string
+  - name: source
+    dtype: string
+  - name: sentence_1
+    dtype: string
+  - name: sentence_2
+    dtype: string
+  - name: label
+    dtype: float32
+  - name: binary-label
+    dtype: float32
+  splits:
+  - name: train
+    num_bytes: 1675390
+    num_examples: 9324
+  - name: validation
+    num_bytes: 97959
+    num_examples: 550
+  download_size: 1657856
+  dataset_size: 1773349
+---

boost_camp.py

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+import csv
+import datasets
+from datasets.download.download_manager import DownloadManager
+
+_CITATION = """"""
+_DESCRIPTION = "hugging face dataset 공유해보기 연습"
+_LICENSE = "CC-BY-SA-4.0"
+_URL = "https://github.com/KyungHyunLim/hf_dataset_test"
+_DATA_URLS = {
+    "train": "https://huggingface.co/datasets/KHLim/boost_camp/resolve/main/train.csv",
+    "valid": "https://huggingface.co/datasets/KHLim/boost_camp/resolve/main/dev.csv"
+}
+
+_VERSION = "0.0.0"
+
+class MyDataConfig(datasets.BuilderConfig):
+    def __init__(self, data_url, **kwargs):
+        super().__init__(version=datasets.Version(_VERSION), **kwargs)
+        self.data_url = data_url
+
+class MYData(datasets.GeneratorBasedBuilder):
+    DEFAULT_CONFIG_NAME = "mydata"
+    BUILDER_CONFIGS = [
+        MyDataConfig(
+            name="mydata",
+            data_url=_DATA_URLS,
+            description=_DESCRIPTION
+        )
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "source": datasets.Value("string"),
+                    "sentence_1": datasets.Value("string"),
+                    "sentence_2": datasets.Value("string"),
+                    "label": datasets.Value("float"),
+                    "binary-label": datasets.Value("float")
+                }
+            ),
+            homepage=_URL,
+            license=_LICENSE,
+            citation=_CITATION,
+            supervised_keys=None,
+        )
+    
+    def _split_generators(self, dl_manager: DownloadManager):
+        data_file = dl_manager.download_and_extract(self.config.data_url)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "data_file": data_file['train'],
+                    "split": "train"
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "data_file": data_file['valid'],
+                    "split": "valid"
+                }
+            )
+        ]
+    
+    def _generate_examples(self, data_file:str, split:str):
+        with open(data_file, newline='', encoding='utf-8') as f:
+            reader = csv.reader(f, delimiter=',')
+            features_names = next(reader)
+            idx = 0
+            for row in reader:
+                features = {
+                    "id": row[0],
+                    "source": row[1],
+                    "sentence_1": row[2],
+                    "sentence_2": row[3],
+                    "label": row[4],
+                    "binary-label": row[5]
+                }
+                yield idx, features
+                idx += 1

dummy/mydata/0.0.0/dummy_data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:37d2d53b94777551d18c345efcba70e0e2339e91fdd19651e82e2eed660e11e7
+size 1185