init commit

README.md

@@ -1,3 +1,12 @@
 ---
 license: lgpl-3.0
+language: es
 ---
+
+# Spanish poems for GPT finetuning
+
+Collection of Spanish poems from www.poemas-del-alma.com.
+
+The `poemas.txt` file has been formatted with special tokens for CLM training.
+
+Titles and author names have been removed, leaving only the poem's body.

poemas.py

@@ -0,0 +1,49 @@
+"""
+### Spanish Poetry Dataset ###
+Collection of Spanish poems retrieved by Andrea Morales and Miguel López from the website www.poemas-del-alma.com
+Corpus adapted for Causal Language Modeling (CLM) to train GPT-like models. The author and title of each poem has been removed.
+Note that, depending on your tokenizer, you might want to replace the <BOS>/<SEP>/<EOS> tokens by <|endoftext|> or something else.
+Also note that the number of rows is slightly lower than the original dataset (andreamorgar/spanish_poetry) because a few incorrect examples have been filtered out.
+"""
+
+import datasets
+
+_DESCRIPTION = "Collection of Spanish poems retrieved from www.poemas-del-alma.com"
+_HOMEPAGE    = "https://www.kaggle.com/datasets/andreamorgar/spanish-poetry-dataset"
+_AUTHORS     = "Andrea Morales and Miguel López"
+_LICENSE     = "GNU Lesser General Public License"
+
+class Poemas(datasets.GeneratorBasedBuilder):
+    def _info(self):
+        features = datasets.Features(
+            {
+                "text": datasets.Value("string"),
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_AUTHORS,
+        )
+
+    def _split_generators(self, dl_manager):
+        data_file = dl_manager.download_and_extract("poemas.txt")
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": data_file,
+                    "split": "train",
+                },
+            )
+        ]
+
+    def _generate_examples(self, filepath, split):
+        to_replace = {"<BOS>": "", "<EOS>": "", "<SEP>": "\n"}
+        with open(filepath, encoding="utf-8") as f:
+            for key, poem in enumerate(f.readlines()):
+                for old,new in to_replace.items():
+                    poem = poem.replace(old, new)
+                yield key, {"text": poem.strip()}