text and sum in one file

.gitattributes

@@ -52,3 +52,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.jpg filter=lfs diff=lfs merge=lfs -text
 *.jpeg filter=lfs diff=lfs merge=lfs -text
 *.webp filter=lfs diff=lfs merge=lfs -text
+data/ami-summary.tar.gz filter=lfs diff=lfs merge=lfs -text

ami-summary.py

@@ -0,0 +1,69 @@
+import datasets
+import os
+
+_DESCRIPTION = """\
+Dataset of meeting transcriptions and summaries of AMI courpus.
+"""
+
+_CITATION = """\
+@InProceedings{Zhu_2015_ICCV,
+    title = {AMI for summarization task},
+    author = {Filipp Abapolov},
+    month = {Fubruary},
+    year = {2023}
+}
+"""
+
+_REPO = "https://huggingface.co/datasets/pheepa/ami-summary/resolve/main"
+_URL = f"{_REPO}/data/ami-summary.tar.gz"
+
+
+class AmiSummary(datasets.GeneratorBasedBuilder):
+    """AmiSummary dataset."""
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name='ami-summary',
+            version=datasets.Version("1.0.0"),
+            description=_DESCRIPTION
+        )
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "text": datasets.Value("string"),
+                    "summary": datasets.Value("string")
+                }
+            ),
+            supervised_keys=None,
+            citation=_CITATION
+        )
+
+    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_ami.txt")}
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"filepath": os.path.join(data_dir, "test_ami.txt")}
+            )
+        ]
+
+    def _generate_examples(self, filepath):
+        """Yields examples."""
+        with open(filepath, 'r') as f:
+            lines = f.read().split('\n')
+        pairs = []
+        for i in range(0, len(lines), 2):
+            pairs.append((lines[i], lines[i + 1]))
+
+        for i, comment in enumerate(pairs):
+            yield i, {'text': pairs[0], 'summary': pairs[1]}