First init

.gitattributes

@@ -35,3 +35,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.mp3 filter=lfs diff=lfs merge=lfs -text
 *.ogg filter=lfs diff=lfs merge=lfs -text
 *.wav filter=lfs diff=lfs merge=lfs -text
+*.jsonl filter=lfs diff=lfs merge=lfs -text

test.jsonl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:be06ecec97fc6c6c52c845dfaa42b6a6e8c8001e805171ea7c1557e98085d3eb
+size 57089045

vilasum.py

@@ -0,0 +1,77 @@
+# Loading script for the VilaSum dataset.
+import json
+import datasets
+
+logger = datasets.logging.get_logger(__name__)
+
+_CITATION = """
+
+            """
+
+_DESCRIPTION = """
+                               """
+
+_HOMEPAGE = """
+"""
+
+#_URL = "https://huggingface.co/datasets/projecte-aina/vilasum/tree/main"
+_URL = '/home/ona/Documents/Summarization/summ_ca/vilaweb_hf/vilasum/'
+_TEST_FILE = "test.jsonl"
+
+class VilaSumConfig(datasets.BuilderConfig):
+    """ Builder config for the VilaSum dataset """
+
+    def __init__(self, **kwargs):
+        """BuilderConfig for VilaSum.
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(VilaSumConfig, self).__init__(**kwargs)
+
+
+class VilaSum(datasets.GeneratorBasedBuilder):
+    """VilaSum Dataset."""
+
+    BUILDER_CONFIGS = [
+        VilaSumConfig(
+            name="VilaSum",
+            version=datasets.Version("1.0.0"),
+            description="VilaSum dataset",
+        ),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "summary": datasets.Value("string"),
+                    "text": datasets.Value("string"),
+                }
+       
+            ),
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+        )
+        
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        urls_to_download = {
+            "test": f"{_URL}{_TEST_FILE}"
+        }
+        downloaded_files = dl_manager.download_and_extract(urls_to_download)
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
+        ]
+
+    def _generate_examples(self, filepath):
+        """This function returns the examples in the raw (text) form."""
+        logger.info("generating examples from = %s", filepath)
+        with open(filepath, encoding="utf-8") as f:
+            for id_, row in enumerate(f):
+                article = json.loads(row)
+                text = article['text']
+                summary = article['summary']
+                yield id_, { "summary": summary,"text": text}